Few studies have been carried out with the specific aim of looking at customer-to-customer (C2C) interaction, as opposed to the co-creation of the experience. There are C2C literature on empirical case studies and conceptual methods, but one approach is to identify and explore a wider range of C2C-driven services in terms of customers’ interaction. In this research we use the framework of agent...

Purpose The purpose of this paper is to empirically examine supplier selection among smalland medium-sized firms in the US textile and apparel industry. For smalland medium-sized firms, one powerful method of improving the firm’s competitiveness in the dynamic business environment is through strategic approach of supplier selection, which emphasizes supplier’s contributions to the total product...

Effective and correct customer classification plays a key role in analyzing and estimating customer consumption patterns, establishing personalized marketing service system and differentiation management. A new customer classification algorithm is advanced based on ant colony algorithm. Firstly, based on consumer characteristics and behaviors analysis, an indicator system is designed which incl...

Correctly and effectively customer classification according to their characteristics and behaviors will be the most important resource for electronic marketing and online trading of network enterprises. Aiming at the shortages of the existing K-means algorithm of data-mining for customer classification, this paper advances a new customer classification algorithm through improving the existing K...

delivering perishable products to customers as soon as possible and with the minimum cost has been always a challenge for producers and has been emphasized over recent years due to the global market becoming more competitive. in this paper a multi-objective mix integer non-linear programming model is proposed to maximize both profits of a distributer and the total freshness of the several produ...

We propose a linearly penalized support vector machines (LP-SVM) model for feature selection. Its application to a problem of customer retention and a comparison with other feature selection techniques underlines its effectiveness.

Typical methods in CRM marketing include action selection on the basis of Markov Decision Processes with fixed transition probabilities on the one hand, and scoring customers separately in pre-defined segments on the other. This points to a gap in the usual methodology insofar as customer scoring implies the explicit use of customer-specific information (covariates), while transition probabilit...

Firms in multiple industries collect customer satisfaction data to measure service performance. Increasingly, however, many firms are now able to collect objective service performance data as well. This raises the question of whether measuring customer satisfaction is valuable to firms when objective service performance data are available. The authors answer this question via the use of unique ...