Strategic Product/Service Innovations of an Online Firm

We study the incentives that drive an online firm to make various types of innovations in a competitive environment. We develop and use a simplified price competition model between two retailers, one online and one offline. A given fraction of consumers, called the Internet penetration, comparison shop online, independent of their customer type, thereby creating two markets for the offline retailer, a captive market and a competitive market. The online product has the steeper of the two linear utility functions, which means that the customers who buy online in our model are high end. We focus on the competitive region in which both retailers are (strictly) profitable in the competitive market and consider innovations that increase high‐end appeal, low‐end appeal, and/or reduce unit cost. We find that the online firm has a strong incentive to invest in innovations that either reduce unit cost and/or, equivalently, increase the appeal to all consumers equally. Investments of this type are strategic complements: implementing one increases the value of another, so the value of two innovations of this type is more than the sum of the values of each individually. We identify a relative strength measure of the online firm such that, as its high‐end appeal increases and/or its unit cost decreases, we say that the online firm is stronger. This strength measure facilitates drawing an explicit dividing line between strong and weak online firms. If Internet penetration increases, the online firm's profits increase if and only if it is strong. If penetration increases over time, it is possible for a strong firm to turn weak and see its profits decrease and possibly disappear completely. A strong online firm has more opportunity to profit from low‐end innovations than does a weak one, while the opposite is true for high‐end innovations. Interestingly, some innovations may actually decrease the online firm's profits. We discuss the implications of our results for existing and future online innovations.     

A Mathematical Model of Service Failure and Recovery Strategies*

Understanding the nature of service failures and their impact on customer responses and designing cost‐effective recovery strategies have been recognized as important issues by both service researchers and practitioners. We first propose a conceptual framework of service failure and recovery strategies. We then transform it into a mathematical model to assist managers in deciding on appropriate resource allocations for outcome and process recovery strategies based on customer risk profiles and the firm's cost structures. Based on this mathematical model we derive optimal recovery strategies, conduct sensitivity analyses of the optimal solutions for different model parameters, and illustrate them through numerical examples. We conclude with a discussion of managerial implications and directions for future research.     

From Amazon to Apple: Modeling Online Retail Sales,Purchase Incidence,and Visit Behavior

In this study, we propose a multivariate stochastic model for Web site visit duration, page views, purchase incidence, and the sale amount for online retailers. The model is constructed by composition from carefully selected distributions and involves copula components. It allows for the strong nonlinear relationships between the sales and visit variables to be explored in detail, and can be used to construct sales predictions. The model is readily estimated using maximum likelihood, making it an attractive choice in practice given the large sample sizes that are commonplace in online retail studies. We examine a number of top-ranked U.S. online retailers, and find that the visit duration and the number of pages viewed are both related to sales, but in very different ways for different products. Using Bayesian methodology, we show how the model can be extended to a finite mixture model to account for consumer heterogeneity via latent household segmentation. The model can also be adjusted to accommodate a more accurate analysis of online retailers like apple.com that sell products at a very limited number of price points. In a validation study across a range of different Web sites, we find that the purchase incidence and sales amount are both forecast more accurately using our model, when compared to regression, probit regression, a popular data-mining method, and a survival model employed previously in an online retail study. Supplementary materials for this article are available online.     

中国企业的"非市场营销"表现及原因分析

本文认为,中国企业广告大战与价格大战的“非市场营销”的表现,其缘由是“边缘化”的经济地位与符码化的消费时尚。它提醒我们,今天的中国企业能够获得的利润有限,还不能像美国的企业那样“一掷千金”地“玩营销”;在西方文化横行天下的今天,在与文化紧密相关的符码方面,处于文化转型的中国还不具有竞争优势。     

基于灰色马尔可夫组合模型的福州港吞吐量预测

灰色马尔可夫组合模型是将灰色预测模型与马尔可夫模型进行组合优化,通过其对福州港2012-2016年货物吞吐量及集装箱吞吐量进行预测,并利用残差模型检验,证明了灰色马尔可夫组合模型能够解决单一模型的局限性、粗糙性和不稳定性问题,预测精度高,符合事物的发展规律,对业界预测港口吞吐量具有实践意义和参考价值。     

吉林省高技术产业与经济增长关联性的实证分析

采用灰色关联分析,对1995至2007年间吉林省高技术产业发展和经济增长的关联性进行实证分析,从高技术产业与其他产业横向对比进行关联系数测算,测算结果表明,吉林省高技术产业灰色关联度为1,作为主导力量拉动吉林省经济增长。     

年代的烙印——从《道连格雷的画像》看文化背景变迁对翻译的影响

本文选取王尔德的小说《道连格雷的画像》,以荣如德1982年的译本,与黄源深2004年的译本做比较,抽取两译本一些造词遣句的译例以及译注,从细微处分析文化背景变迁对这部小说翻译的影响,从而揭示了译本必然与其所处的社会大环境有紧密关系。     

“情理营销”与“法理营销”:中国营销理论发展过程中若干问题思考

从中美文化价值体系和行为规范的差异出发,沿着"坐‘井’观‘天’—‘水’中捞‘月’—探‘囊’取‘物’—‘管’中窥‘豹’"的思路,探讨情理营销与法理营销的理论概念。在此基础上,探讨该概念对跨文化背景下的营销研究所具有的借鉴意义,以及中国营销理论发展过程中的若干问题。     

Supply chain configuration for diffusion of new products: An integrated optimization approach

We develop an integrated/hybrid optimization model for configuring new products’ supply chains while explicitly considering the impact of demand dynamics during new products’ diffusion. The hybrid model simultaneously determines optimal production/sales plan and supply chain configuration. The production and sales plan provides decisions on the optimal timing to launch a new product, as well as the production and sales quantity in each planning period. The supply chain configuration provides optimal selection of options and safety stock level kept at each supply chain function. Extensive computational experiments on randomly generated testbed problems indicate that the hybrid modeling and solution approach significantly outperforms non-hybrid alternative modeling and solution approaches under various diffusion and supply chain topologies. We provide insights on optimal production/sales plan and supply chain configuration for new products during their diffusion process. Also, managerial implications relevant to effectiveness of the hybrid approach are discussed.