We introduce three types of consumer recognition: identity recognition, asymmetric preference recognition, and symmetric preference recognition. We characterize price equilibria and compare profits, consumer surplus, and total welfare. Asymmetric preference recognition enhances profits compared with identity recognition, but firms have no incentive to exchange information regarding customer-spe...

In this paper, customer restaurant preference is predicted based on social media location check-ins. Historical preferences of the customer and the influence of the customer’s social network are used in combination with the customer’s mobility characteristics as inputs to the model. As the popularity of social media increases, more and more customer comments and feedback about products and serv...

In retail operations, customer choices may be affected by stockout and promotion events. Given panel data with the transaction history of customers, and product availability and promotion data, our goal is to predict future individual purchases. We use a general nonparametric framework in which we represent customers by partial orders of preferences. In each store visit, each customer samples a...

Excerpt] The purpose of this chapter is to present a model that integrates customer preferences and service design. In response to the need for interdisciplinary service management research, we present a framework that specifies the key elements of an integrated market utility-based model (MUM) and a method for determining optimal service designs based on customer needs and preferences. We also...

Communication services are currently confronted with large changes due to the price erosion of services and entering new service providers. The gap is filled with different services that are hoped to be successful in the near future. The problem, however, is that firms do not necessarily know what their customers value. One solution to the problem is building a customer value model. This paper ...

We present an implemented customer oriented online shopping system called HOPE (Helpful Online Purchase Environment). Data mining methods are used to automatically generate suggestions, which vary according to the customer and section being browsed. Customers receive personalized suggestions that match their own purchasing habits and preferences.

Quality function deployment (QFD) help to realize significant reduction in product design cost and development time. The QFD process includes ranking customer preferences, rating the competitors, and parts deployment for the new or existing product. This study is carried out to understand the QFD concepts and implement this concept into the redesign of Monoblock submersible pump according to th...

Firms routinely use behavior based pricing (BBP), to segment customers by past purchase behavior. This paper answers a dilemma facing such firms – When should the firm reward existing customers as opposed to new customers? Further, the paper sheds insight on when behavior based pricing will increase or decrease profits in a competitive market. The analysis adds two features of customer behavior...

In this paper we propose a theoretical data mining framework for automatic gathering of consumer data for companies interested in developing product prototypes based on customer needs and preferences; we also provide automatic methods for discovering the relationships between customers’ preferences and the product’s physical characteristics. The current framework is presented for the automotive...

This paper proposes a method to construct Behavior Targeting, which is an effective advertising method for Web Publishers. One of the challenges on constructing Behavior Targeting is the heavy load on the hardware when extracting customer preference information due to the enormous number of customers and the extremely broad areas that the customers might be interested in. We address this proble...