Optimal software pricing in the presence of piracy and word-of-mouth effect

We develop an analytical model that embeds empirical findings on software diffusion to examine optimal pricing strategies for a spreadsheet software product under coalescing effects of piracy and word-of-mouth through its entire life cycle. We find that the demand of the innovators has the most significant impact on the firm's pricing decision. Our research recommends market skimming pricing strategy if innovators' demand is high and the market penetration pricing strategy is preferred otherwise. Surprisingly, the increase of conversion rate of imitators to buyers never significantly alters the pricing strategy pre-determined by the demand of innovators. Most interestingly, the optimal profit from instituting a two prices policy for a software product with five years lifespan outperforms that from a one price policy by no more than 4%, a finding that corroborates the common one price policy observed in reality.     

A modified Lotka–Volterra model for competition forecasting in Taiwan’s retail industry

The retail industry is an important component of the supply chain of the goods and services that are consumed daily and competition has been increasing among retailers worldwide. Thus, forecasting the degree of retail competition has become an important issue. However, seasonal patterns and cycles in the level of retail activity dramatically reduce forecasting accuracy. This paper attempts to develop an improved forecasting methodology for retail industry competition subject to seasonal patterns and cycles. Using market share data and the moving average method, a modified Lotka–Volterra model with an additional constraint on the summation of market share is proposed. Furthermore, the mean absolute error is used to measure the forecasting accuracy of the market share. Real Taiwanese retail data from 1999 is used to validate the forecasting accuracy of our modified Lotka–Volterra model. Our methodology successfully mitigates errors from seasonal patterns and cycles and outperforms other benchmark models. These benchmarks include the Bass and Lotka–Volterra models for revenue or market share data, with or without using the moving average method. Our methodology assists the retail industry in the development of management strategies and the determination of investment timing. We also demonstrate how the Lotka–Volterra model can be used to forecast the degree of industry competition.     

A simulation‐based algorithm for optimal pricing policy under demand uncertainty

We propose a simulation‐based algorithm for computing the optimal pricing policy for a product under uncertain demand dynamics. We consider a parameterized stochastic differential equation (SDE) model for the uncertain demand dynamics of the product over the planning horizon. In particular, we consider a dynamic model that is an extension of the Bass model. The performance of our algorithm is compared to that of a myopic pricing policy and is shown to give better results. Two significant advantages with our algorithm are as follows: (a) it does not require information on the system model parameters if the SDE system state is known via either a simulation device or real data, and (b) as it works efficiently even for high‐dimensional parameters, it uses the efficient smoothed functional gradient estimator.     

Manufacturing production plan optimization in three-stage supply chains under Bass model market effects

The Bass model is a very successful parametric approach to forecast the diffusion process of new products. In recent years, applications of the Bass model have been extended to other operational research fields such as managing customer demands, controlling inventory levels, optimizing advertisement strategies, and so forth. This study attempts to establish an application for optimizing manufacturers’ production plans in a three-stage supply chain under the Bass model’s effects on the market. The supply chain structure considered in this research is similar to other common supply chains comprised of three stages, namely retailer, distributor and manufacturer. The retailer stage has to handle customer demands following the Bass diffusion process. Market parameters and essential information are assumed to be available and ready for access. Each stage is expected to determine its inventory policy rationally. That is, each stage will attempt to maximize its own profits. These decisions will back-propagate their effects to upper stages. This study adopts a dynamic programming approach to determine the inventory policies of each stage so as to optimize manufacturers’ production plans.     

Bernard (Bernie) M. Bass (1925-2007).

Bernard M. Bass, distinguished professor emeritus in the School of Management at Binghamton University, was born on June 11, 1925, in the Bronx, New York, and died in Binghamton, New York, on October 11, 2007, at the age of 82. Bass published more than 400 journal articles and technical reports, wrote 21 books, and edited an additional 10. Almost all of his published work dealt with issues of leadership and organizational behavior. Before his death, Bass completed the authoritative resource book in leadership, the fourth edition of the Bass handbook of leadership. In the field of organizational behavior, leadership, and human resource management, there is hardly a niche in which Bass did not have an impact. Over his long career, he mentored many people who have and will continue to carry on his good work. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

专利引文影响下的混合动力汽车创新扩散研究

把专利间的引用关系看作技术扩散,并将其引入Bass扩散模型,构建含有技术扩散影响因素的改进模型。利用普瑞斯的销售数据和丰田公司被引专利数据,对原始模型及改进模型作了非线性最小二乘法估计。结果表明,技术扩散能够影响消费者购买新产品的愿望,改进模型对HEV扩散的拟合度优于原始模型。     

小型扬声器感知低音的生成算法优化

虚拟低音技术针对扬声器低频重放问题提供了一种较好的处理方式,其建立在“虚拟音高”理论基础上,将扬声器输入信号在不能重放的低频部分利用其高次谐波成分在听感上虚拟出基频音高.考虑到小型扬声器频带窄、失真大等特性,在虚拟低音的相位声码器算法基础上,用二阶求导的方式对频谱低频峰值进行取点,对不同频段生成不同的谐波个数,简化幅度控制,提出适合于小型扬声器的低音谐波生成模块优化算法并实现.主观实验结果表明改进后的算法在增强低音效果的同时也能保证较好的整体音质效果.     

基于Bass模型的超临界机组和超超临界机组的扩散情景分析

本文在Bass模型原理的基础上,建立了关于政府投资、成本对超临界机组和超超临界机组的扩散影响模型,同时考虑了超临界机组和超超临界机组的竞争。研究发现：（1）超临界机组和超超临界机组的成本,对其扩散影响较小,而政府投资对超临界机组和超超临界机组的扩散影响较大;（2）在1.5倍和2倍于当前投资情景下,不同政府投资影响率下（Q值不同）,超临界机组的最大市场装机容量分别为494.59,558.39,622.20 GW和434,518,602 GW,而超超临界机组的分别为905.42,841.61,777.81 GW和966,882,798 GW;(3)超临界机组和超超临界机组都将在2025年左右完成扩散过程。     

几种巴斯模型参数估计方法的比较研究

在创新扩散的巴斯模型的基础上,提出了一种新的模型参数估计方法--采用蚁群算法作为巴斯模型参数估计方法.给出了运用蚁群算法思想设计的具体参数估计方法,并以中国移动通信技术的扩散为例,应用巴斯模型对其扩散趋势进行了实证研究,通过对蚁群算法和最小二乘法、遗传算法等传统参数估计方法估计结果的比较分析,得出结论,采用蚁群算法作为巴斯模型的参数估计方法效果更好.最后对中国移动通信技术的扩散趋势进行了预测并提出策略建议.     

Regional difference of residential solar panel diffusion in Queensland,Australia

ABSTRACT

In recent years, the regional difference of residential solar panel adoption has raised the concern on energy justice and also elicited a fundamental question on how the distribution of access to solar energy services should occur in the society. Focusing on Queensland, a sunshine state in Australia, this study used the generalized Bass diffusion model to investigate and compare how, why, and at what rate solar panels spread in densely and sparsely populated areas. The results highlight that the spreading of solar panels lies in the imitation effect, in which a household’s solar adoption is susceptible to the behaviors or comments of its neighbors, and this effect is stronger in highly populated areas. Furthermore, the highly populated areas are also more sensitive to the market price change. In contrast, there is a lack of imitation effect and market sensitivity in the sparsely populated areas. For policymakers, it is necessary to consider these regional differences in the solar energy development; a stronger promulgation agenda is needed from the government to cultivate the adoption culture in those sparsely populated areas.