How should a firm design a price/lead-time menu and scheduling policy to maximize revenues from heterogeneous time-sensitive customers with private information about their preferences? We consider a queueing system with multiple customer types that differ in their valuations for instant delivery and their delay cost rates. The distinctive feature of our model is that the ranking of customer pre...

In a market with rapid changes in technology and customer preferences, technological obsolescence of end-of-life products poses a significant challenge to product recovery. Remanufacturing with optimal part upgrades can be a promising solution for overcoming the obsolescence. This paper proposes a model for positioning a remanufactured product. By considering original product design, target mar...

Customer satisfaction depends on many variables, such as quality, price, availability, customer service, and so on, and increases with the degree to which the delivered product meets the customer’s preferences. Frequently, vendors have to help customers select a product from among those available to satisfy their needs and wants. Most of the time, the information provided by the customers is no...

INtrODUctION Customer relationships are increasingly central to business success (Kotler, 1997; Reichheld & Sasser, 1990). Acquiring new customers is five to seven times costlier than retaining existing customers (Kotler, 1997). Simply by reducing customer defec-tions by 5%, a company can improve profits by 25% to 85% (Reichheld & Sasser, 1990). Relationship marketing—getting to know customers ...

Organizations have been forced to transform themselves from “product-centric” to “customer-centric” for various reasons. Becoming customer centric is one of the most important aims of any organization. Customer Relationship Management has attracted the attention of both marketing practitioners and researchers over the last decade. Despite, or maybe due to, the attention drawn to the subject, a ...

In this ever changing business scenario, success of the company lies in understanding the customer preferences, tastes and anticipating the changes required in existing or new products being offered. It was desired to develop a model which allows decision makers to decompose a complex problem in a hierarchical structure to show the relationship of the goals, objectives, criteria and alternative...

The rows of the design matrix in linear regression are the inputs of the training data set. Normal regression is row regression: the goal is to predict a training target from the corresponding row in the design matrix using a linear model. In contrast, in column regression we predict the components of the test input from the corresponding columns of the design matrix using a linear model and th...

Data governance (DG) has emerged as the primary tool for assuring that the information assets of an enterprise are managed in compliance with a uniform set of policies and procedures. DG is still an evolving practice, but several processes and systems are generally regarded as standard components of DG. For example, a business glossary, data dictionaries, a data quality program, and master data...

We present a new XML-based search technology for e-commerce that enables users to formulate complex customer or vendor preferences, which typically occur within B2C or B2B applications. Preferences are modeled in a very natural way by partial orders. Since our semantics of multi-attribute preferences implements the Pareto-optimality principle, Preference XPATH queries avoid both the unwanted "e...

T study attempts to answer a basic customer management dilemma facing firms: when should the firm use behavior-based pricing (BBP) to discriminate between its own and competitors’ customers in a competitive market? If BBP is profitable, when should the firm offer a lower price to its own customers rather than to the competitor’s customers? This analysis considers two features of customer behavi...