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

An Architecture for Information Commerce Systems

The increasing use of the Internet in business and commerce has created a number of new business opportunities and the need for supporting models and platforms. One of these opportunities is information commerce (i-commerce), a special case of ecommerce focused on the purchase and sale of information as a commodity. In this paper we present an architecture for i-commerce systems using OPELIX (Open Personalized Electronic Information Commerce System) [11] as an example. OPELIX provides an open information commerce platform that enables enterprises to produce, sell, deliver, and manage information products and related services over the Internet. We focus on the notion of information marketplace, a virtual location that enables i-commerce, describe the business and domain model for an information marketplace, and discuss the role of intermediaries in this environment. The domain model is used as the basis for the software architecture of the OPELIX system. We discuss the characteristics of the OPELIX architecture and compare our approach to related work in the field

The Potential of Critical E-Applications for Engaging SMEs in E Business: A Provider Perspective

YesAgainst a background of the low engagement of SMEs in e-business this paper investigates the emergence of, and potential for, critical e-applications defined as `an e-business application, promoted by a trusted third party, which engages a significant number of SMEs by addressing an important shared business concern within an aggregation.¿ By a review of secondary data and empirical investigation with service providers and other intermediaries the research shows that such applications can facilitate the e-business engagement of SMEs. There are three key findings, namely: the emergence of aggregation specific e-business applications; the emergence of collaboratively based `one to many¿ business models; and the importance of trusted third parties in the adoption of higher complexity e-business applications by SMEs. Significantly this work takes a deliberately provider perspective and complements the already considerable literature on SME IT adoption from a user and network perspective. In terms of future research the importance of a better conceptual understanding of the impact of complexity on the adoption of IT by SMEs is highlighted

From physical marketing to web marketing

Reviews the criticism of the 4P marketing mix framework as the basis of traditional and virtual marketing planning. Argues that the customary marketing management approach, based on the popular marketing mix 4Ps paradigm, is inadequate in the case of virtual marketing. Identifies two main limitations of the marketing mix when applied in online environments namely the role of the Ps in a virtual commercial setting and the lack of any strategic elements in the model. Identifies the critical factors of the Web marketing and argues that the basis for successful e-commerce is the full integration of virtual activities into the company's physical strategy, marketing plan and organisational processes. The 4S elements of the Web marketing mix framework offer the basis for developing and commercialising business to consumer online projects. The model was originally developed for educational purposes and has been tested and refined by means of three case studies

Generating citizen trust in e-government using a trust verification agent: A research note

Generating Citizen Trust in e-Government using a Trust Verification AgentThis is an eGISE network paper. It is motivated by a concern about the extent to which trust issues inhibit a citizen’s take-up of online public sector services or engagement with public decision and policy making. A citizen’s decision to use online systems is influenced by their willingness to trust the environment and agency involved. This project addresses one aspect of individual “trust” decisions by providing support for citizens trying to evaluate the implications of the security infrastructure provided by the agency. Based on studies of the way both groups (citizens and agencies) express their concerns and concepts in the security area, the project will develop a software tool – a trust verification agent (TVA) - that can take an agency’s security statements (or security audit) and infer how effectively this meets the security concerns of a particular citizen. This will enable citizens to state their concerns and obtain an evaluation of the agency’s provision in appropriate “citizen friendly” language. Further, by employing rule-based expert systems techniques the TVA will also be able to explain its evaluation.Engineering and Physical Sciences Research Council, UK (grant GR/T27020/01

Identifying smart design attributes for Industry 4.0 customization using a clustering Genetic Algorithm

Industry 4.0 aims at achieving mass customization at a mass production cost. A key component to realizing this is accurate prediction of customer needs and wants, which is however a challenging issue due to the lack of smart analytics tools. This paper investigates this issue in depth and then develops a predictive analytic framework for integrating cloud computing, big data analysis, business informatics, communication technologies, and digital industrial production systems. Computational intelligence in the form of a cluster k-means approach is used to manage relevant big data for feeding potential customer needs and wants to smart designs for targeted productivity and customized mass production. The identification of patterns from big data is achieved with cluster k-means and with the selection of optimal attributes using genetic algorithms. A car customization case study shows how it may be applied and where to assign new clusters with growing knowledge of customer needs and wants. This approach offer a number of features suitable to smart design in realizing Industry 4.0