Liu Wenhuang

The Application ofAdaBoost in Customer Churn Prediction

Since attracting new customers is known to be more expensive, the enhancement of existing relationships is of pivotal importance to companies. Therefore, as part of the customer relationship management (CRM) strategy, predicting customer churn and improving customer retention have attracted more and more attention. Being aware of the defection prone customers beforehand, companies could react in time to prevent the churn by offering the right set of products, modifying the sales strategy and providing customized services. Therefore, high predictive performance could ultimately lead to profit increasing for companies. In this paper, we use the AdaBoost which is a main branch of boosting algorithms to predict the customer churn. We have implemented three different boosting schemes: Real AdaBoost, Gentle AdaBoost and Modest AdaBoost. Applied to a credit debt customer database of an anonymous commercial bank in China, they are proven to significantly improve prediction accuracy comparing with other algorithms, like SVM. The assessment and comparison of these algorithms are made to analyze the traits of them. Data processing and sampling scheme are also detailed in this paper.

Research of supply chain decision support system based on self-organization

With the rapid development of information technology and knowledge economy, the global market pattern comes into being accordingly. Most enterprises are dedicated to adopt the advanced supply chain management pattern in order to improve their business management. In this paper a supply chain decision support system based on self-organization is introduced and analyzed in detail; it is a powerful information supporting and system model building tool. The research is made under the typical application background and objectives, and shows the great market application potentiality in the near future.

A blackboard-based multi-agent distributed QFD system

A type of quality function development (QFD) is an important methodology for concurrent engineering. QFD contacts the customer requirements and production process. In distributed environment, customer requirements, multiple team members and process are geographically, culturally, and functionally diverse. It requires cooperation and conflict resolution among design, production and sales process. In this paper, we introduce a blackboard-based multi-agent distributed QFD framework. In this framework, QFD core module, manufacture module, distributed TM module and market module are presented. Agents are used to emulate the entities i.e. various module and their internal departments. The framework facilitates the development of the product design and the production process.

The framework of agent-based concurrent engineering oriented distributed QFD system

Quality function development (QFD) is an important methodology for concurrent engineering. QFD contacts the customer requirements and production process. In distributed environment, customer requirements, multiple team members and process are geographically, culturally, and functionally diverse. It requires cooperation and conflict resolution among design, production and sales process. In this paper, we introduce a multi-agent-based distributed QFD framework, which orients concurrent engineering (MAS-CEQFD). In this framework, QFD core module, manufacture module, distributed TM module and market module are presented. Agents are used to emulate the entities, i.e. various module and their internal departments. The framework facilitates the development of the product design and the production process.

Enterprise competence modeling and management

It is very important for an enterprise to understand its competence and to improve it continuously, so as to better engage with the competitive market environment. This enterprise competence information is also valuable for potential cooperation among different enterprises. However, this information is often not available even within the enterprise itself, let alone for other enterprises, because there is no set of general methods for the modeling and management of enterprise competence. In this paper, we present a competence management system based on a common enterprise competence model (ECM), including a competence modeling method, system architecture, model-based decision support, and a core technology for system implementation.

The solution to a kind of Markov chain CRM model with a constant state keeping probability

Based on the solution to a kind of Markov chain (MC) customer relationship management (CRM) model, the resolve solution of the MC CRM model with the state keeping probability is studied in the paper. By computing the inverse matrix for the equation given, we make a resolve solution for this kind of MC CRM model, then shortly make a comparison between the solutions and CLV (the total expected net present value in customer life cycle) results, with and without such state keeping probability.

The expected net present value solution and their CLV comparison of two kinds of Markov CRM models

Pfeifer model and its variation is the Markov chain(MC) models which should be studied in CRM(customer relationship management) analysis. We study the two kinds of model, in infinite horizon purchasing case, demonstrate their expected net present value (ENPV) solution, make a computing to their corresponding CLV (The total expected net present value in customer life cycle), then make a comparison to the CLV of the two scenarios. The study shows: the CLV will vary with the state keeping probability (SKP) changing, and the CLV in the scenario with the SKP will be better than that of without the item.

Knowledge based decision support system for matchmaking of enterprise competence

When faced with a fast-changing global market, an enterprise needs to understand its own competence clearly, as well as assess its competence correctly according to the market demands. This paper focuses on the matchmaking of enterprise competence with competence requests. We propose a kind of knowledge-based decision support system (DSS) for the problem of competence matchmaking, which uses a multi-agent system. Agents in the system can be requestors or providers of competence, which can take advantage of the knowledge in the competence knowledge base to settle the problem of competence matchmaking through reasoning and interaction with other agents. This DSS has the capability of automatic quantitative reasoning, as well as its knowledge-based decision support capability.