Application of artificial neural network in market segmentation: A review on recent trends

Despite the significance of Artificial Neural Network (ANN) algorithm to market segmentation, there is a need of a comprehensive literature review and a classification system for it towards identification of future trend of market segmentation research. The present work is the first identifiable academic literature review of the application of neural network based techniques to segmentation. Our study has provided an academic database of literature between the periods of 2000-2010 and proposed a classification scheme for the articles. One thousands (1000) articles have been identified, and around 100 relevant selected articles have been subsequently reviewed and classified based on the major focus of each paper. Findings of this study indicated that the research area of ANN based applications are receiving most research attention and self organizing map based applications are second in position to be used in segmentation. The commonly used models for market segmentation are data mining, intelligent system etc. Our analysis furnishes a roadmap to guide future research and aid knowledge accretion and establishment pertaining to the application of ANN based techniques in market segmentation. Thus the present work will significantly contribute to both the industry and academic research in business and marketing as a sustainable valuable knowledge source of market segmentation with the future trend of ANN application in segmentation.Comment: 24 pages, 7 figures,3 Table

Ensemble of Example-Dependent Cost-Sensitive Decision Trees

Several real-world classification problems are example-dependent cost-sensitive in nature, where the costs due to misclassification vary between examples and not only within classes. However, standard classification methods do not take these costs into account, and assume a constant cost of misclassification errors. In previous works, some methods that take into account the financial costs into the training of different algorithms have been proposed, with the example-dependent cost-sensitive decision tree algorithm being the one that gives the highest savings. In this paper we propose a new framework of ensembles of example-dependent cost-sensitive decision-trees. The framework consists in creating different example-dependent cost-sensitive decision trees on random subsamples of the training set, and then combining them using three different combination approaches. Moreover, we propose two new cost-sensitive combination approaches; cost-sensitive weighted voting and cost-sensitive stacking, the latter being based on the cost-sensitive logistic regression method. Finally, using five different databases, from four real-world applications: credit card fraud detection, churn modeling, credit scoring and direct marketing, we evaluate the proposed method against state-of-the-art example-dependent cost-sensitive techniques, namely, cost-proportionate sampling, Bayes minimum risk and cost-sensitive decision trees. The results show that the proposed algorithms have better results for all databases, in the sense of higher savings.Comment: 13 pages, 6 figures, Submitted for possible publicatio

Further Thoughts on CRM

Skepticism and disappointment have replaced the initialenthusiasm about CRM. The disappointing results ofCRM-projects are often related to difficulties thatmanagers encounter in embedding CRM in their strategyand organization structure. In this article we presenta classification scheme on how CRM can be strategicallyembedded in organizations using the value disciplinesof Treacy and Wiersema. We use the findings from threecase studies to illustrate our classification. Based onthese case studies and interviews with managers wedistinguish between strategic and tactical CRM, andderive important issues that managers should considerbefore successfully implementing CRM.customer relationship management;marketing strategy;marketing performance

Competitive Positioning in International Logistics: Identifying a System of Attributes Through Neural Networks and Decision Trees

Firms involved in international logistics must develop a system of service attributes that give them a way to be profitable and to satisfy customers’ needs at the same time. How customers trade-off these various attributes in forming satisfaction with competing international logistics providers has not been explored well in the literature. This study explores the ocean freight shipping sector to identify the system of attributes that maximizes customers’ satisfaction. Data were collected from shipping managers in Singapore using personal interviews to identify the chief concerns in choosing and evaluating ocean freight services. The data were then examined using neural networks and decision trees, among other approaches to identify the system of attributes that is connected with customer satisfaction. The results illustrate the power of these methods in understanding how industrial customers with global operations process attributes to derive satisfaction. Implications are discussed

PREDICTING CROSS-GAMING PROPENSITY USING E-CHAID ANALYSIS

Cross-selling different types of games could provide an opportunity for casino operators to generate additional time and money spent on gaming from existing patrons. One way to identify the patrons who are likely to cross-play is mining individual players’ gaming data using predictive analytics. Hence, this study aims to predict casino patrons’ propensity to play both slots and table games, also known as cross-gaming, by applying a data-mining algorithm to patrons’ gaming data. The Exhaustive Chi-squared Automatic Interaction Detector (E-CHAID) method was employed to predict cross-gaming propensity. The E-CHAID models based on the gaming-related behavioral data produced actionable model accuracy rates for classifying cross-gamers and non-cross gamers along with the cross-gaming propensity scores for each patron. Using these scores, casino managers can accurately identify likely cross-gamers and develop a more targeted approach to market to them. Furthermore, the results of this study would enable casino managers to estimate incremental gaming revenues through cross-gaming. This, in turn, will assist them in spending marketing dollars more efficiently while maximizing gaming revenues

Determinants of the outcomes of services outsourcing: an empirical study of transport services.

The purpose of our study is to examine whether the design and management of the interfaces and interaction processes between customer and provider in services outsourcing are determinants of the results achieved by the outsourcing company. Following the conceptual framework initiated in the study by Wynstra et al. [11], this study focuses on transport services and hypothesized relationships are tested using the Partial Least Squares (PLS) statistical technique. The primary data used was obtained from a survey in three different countries (Germany, Japan and Spain), and from manufacturing companies in the electronics, automotive and machinery sectors. Among other things, the results show that both the structural dimensions of interaction (the organization's resources that it must commit) and the process dimensions of interaction (that consider the dynamic nature of the relationships), are important for obtaining adequate performance from transport services outsourcing.Spanish National Program of Industrial Design and Production DPI 2009 11148PAIDI Excellence Projects P08-SEJ0384

Management Accounting for Service: A Research Agenda

Purpose – The purpose of the paper is to point out a research agenda for Management Accounting under the emergent Service-Dominant (S-D) Logic. S-D Logic is widely discussed in the field of Marketing, the paper tries to extend S-D Logic in the Management Accounting context and develops some related considerations. Methodology/approach – Service related change in economy and firms raises new challenging issues in management accounting topics such as cost classification, cost structure, cost object, the role of “traditional” accounting tools and models, price-cost relations for pricing decisions. In this paper, we identify several critical research questions that address a tentative research agenda in the field of management accounting to better explore its role within service science. Throughout the paper many different examples are provided in order to support what is sustained. Findings – The conclusions of the paper trace some aspects addressed as core in the distinction between Goods-Dominant Accounting and Service-Dominant Accounting. Considering the new changing service environment, the role of management accounting in providing information to support managerial decision making and control can be widely renewed. Research implications – The paper opens many underexplored topics on Management accounting in the interface with service and traces a research agenda for further research. Originality/value – This is the first paper, after the brief overview on accounting and Service Science provided by Kerr (2008), aiming at understanding the role of Management accounting in the context of S-D Logic.Service-Dominant Logic, Management Accounting, Costing, Measurement, Value.