Motivated by practices in customer contact centers, we consider a system that offers two modes of service: real-time and postponed with a delay guarantee. Customers are informed of anticipated delays and select their preferred option of service. The resulting system is a multiclass, multiserver queueing system with state-dependent arrival rates.
This paper has three objectives. First, we develop an equilibrium pricing model in which consumers have incomplete information about both product qualities and prices. Specifically, manufacturers can use high prices to signal high quality to uninformed consumers. Furthermore, prices of any given brand can vary geographically across retail outlets. We show that previous models are special cases of our model. Specifically, the hedonic regression model assumes that consumers have full information about all product qualities and prices.
This study examines whether the quality of online buying experience represents a competitive advantage for Internet firms focused on business to consumer e-commerce (“e-commerce” firms). Forrester Research, a consulting firm, estimates that revenues in the business to consumer segment will grow from $20 billion in 1999 to $184 billion by 2004. Such explosive growth is due, in part, to the superior shopping experiences that new e-commerce firms offer.
We show that network advantages constitute an important intangible asset that goes unrecognized in the financial statements. For a sample of e-commerce firms, we find that network advantages created by Web site traffic have substantial explanatory power for stock prices over and above traditional summary accounting measures such as earnings and book value of equity. Also, network advantages are positively associated with one-year-ahead and two-year-ahead earnings forecasts provided by equity analysis.
This paper is concerned with dynamic control of stochastic processing networks. Specifically, it follows the so called heavy traffic approach, where a Brownian approximating model is formulated, an associated Brownian optimal control problem is solved, the solution of which is then used to define an implementable policy for the original system. A major challenge is the step of policy translation from the Brownian to the discrete network. This paper addresses this problem by defining a general and easily implementable family of continuous-review tracking policies.
As more firms adopt a customer asset management approach to their business, it has become increasingly important to understand how customer management efforts relate to the financial performance of the firm. Of specific interest to shareholders is the relationship between traditional financial measures and customer-centric measures. The customer-centric measure that has received the most attention is customer lifetime value (CLV).
The authors investigate two competing hypotheses about how chronic vividness of imagery interacts with the vividness and salience of information in decision making. Results from four studies, covering a variety of decision domains, indicate that chronic imagery vividness rarely amplifies the effects of vivid and salient information. Imagery vividness may, in fact, attenuate the effects of vivid and salient information. This is because, relative to nonvivid imagers, vivid imagers rely less on information that appears obvious and rely more on information that seems less obvious.
Although diffusion models have been successfully used to predict the adoption patterns of new products and technologies, little research has examined the psychological processes underlying the individual consumers adoption decision. This study uses the knowledge transfer paradigm, studied often in the context of analogies, to demonstrate that both existing knowledge and innovation continuity are major factors influencing the consumers adoption process. In two experiments, the authors demonstrate that the relationship between expertise and adoption is relatively complex.
Several online firms, including Yahoo!, Amazon.com, and Movie Critic, recommend documents and products to consumers. Typically, the recommendations are based on content and/or collaborative filtering methods.