Showing papers in "Journal of Interactive Marketing in 2006"

TL;DR: In this article, the authors report the development of scales to measure the perceived benefits and risks associated with online shopping based on an exploratory qualitative inquiry and quantitative assessment, a four-factor scale of perceived benefits of online shopping and a three-factor scales of perceived risks were developed.

TL;DR: In this paper, the authors focus on time planning style, an individual's habitual approach to time management, in relation to the use of the Web and provide empirical evidence that highly analytic versus spontaneous planners are more likely to seek utilitarian rather than hedonic benefits from Web use.

TL;DR: In this paper, a process view of personalization is presented, showing how the different phases of personalisation, including customer interactions, analyses of customer data, customization based on customer profiles, and targeting of marketing activities are linked.

TL;DR: In this article, a two-stage approach for dynamically deriving behaviorally persistent segments and subsequent target marketing selection using retail-purchase histories from loyalty-program members is proposed.

TL;DR: In this article, the authors attempt to organize consumer behavior into streams of research that address the development of marketplaces for the digital economy, arguing that the unbundling of product information from products presents many decisions and opportunities for the design of decision environments.

TL;DR: In this paper, the authors compare price differences and market dynamics between two types of online retailers: online branches of multichannel retailers (OBMCRs) and pure Internet retailers (Dotcoms), based on a set of panel data collected from the DVD market.

TL;DR: In this article, the authors discuss a two-step procedure comprising adaptive learning and proactive CRM decisions, and formulate CRM interventions as solutions to a stochastic dynamic programming problem under demand uncertainty in which the company learns about the evolution of customer demand as well as the dynamic effect of its marketing interventions, and make optimal CRM decision to balance the cost of interventions and the long-term payoff.

TL;DR: In this paper, the authors developed a hazard modeling approach to predict customer churn and study the nature of the empirical link between churn and factors such as customer service experience, failure recovery, and payment equity.

TL;DR: In this paper, a large-scale field experiment was conducted at an informational web site where the timing of pop-up promotions being offered was varied, and the experiment examined the Web user's reaction to the promotion in terms of a direct response to the promotions (i.e., clickthrough) and any indirect response in the user's Web-site-exit behavior.

TL;DR: In this paper, the authors investigated the relationship between e-tail success and the number of product categories sold and the presence of features that allow shoppers to search for products. And they found that while successful e-commerce sites typically added service-related features between 2000 and 2004, these etailers reduced shoppers' contact ability over these years.

TL;DR: In this paper, the authors developed an analytical model to address three questions: under what product-market conditions should the seller offer the magazine content online? What assortment of online forms (bundle, unbundled modules, or both) is optimal? What are the pricing implications?

TL;DR: In this article, a proportional hazard model is used with time-varying usage covariates obtained from Web logs while controlling for initial purchase characteristics such as purchase price and billing frequency.

TL;DR: In this paper, a customized pricing strategy based on heterogeneous price thresholds estimated from scanner panel data is explored and the expected incremental profits from customized discounting as well as customized price hike are evaluated using hierarchical Bayes modeling with the Markov chain Monte Carlo method.

TL;DR: This article proposes an analytical engine that combines techniques from statistical market response modeling, datamining, and combinatorial optimization to produce a small, efficient rule set that predicts sales volume levels.

TL;DR: In this paper, a real-world application of customer development and retention on a Web-banking site using clickstream data from a financial institution in The Netherlands is presented, where it is shown that visitors and customers differ in online development over time.

TL;DR: In this article, customer relationship management (CRM) is viewed as the business process in which customer equity (i.e., aggregate lifetime value of a firm's existing and potential customers) is continuously created, enhanced, and managed by interacting with customers through multiple channels.

TL;DR: This work proposes location-based dynamic targeting of customers by proposing spatial models of choice that adapt to dynamically changing environments and shows that learning models have superior predictive capabilities over a pure static approach and thus are ideally suited for dynamic environments.