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PurposeThe purpose of this survey research is twofold. First, to study and report the process that is commonly used to create and maintain a competitive intelligence (CI) program in organizations. And second, to provide an analysis of several emergent text mining, web mining and visualization‐based CI tools, which are specific to collection and analysis of intelligence.Design/methodology/approachA range of recently published research literature on CI processes, applications, tools and technologies to collect and analyze competitive information within organizations is reviewed to explore their current state, issues and challenges learned from their practice.FindingsThe paper provides executive decision makers and strategic managers a better understanding of what methods are available and appropriate to the decisions they must make and the steps involved in CI undertaking.Originality/valueThe findings of this research provide the managers of CI programs a context for understanding which tools and techniques are better suited to their specific types of problems; and help them develop and evaluate a usable set of tools and best practices to apply to their industry.

Purpose -Advanced analytics-driven data analyses allow enterprises to have a complete or "360 degrees" view of their operations and customers. The insight that they gain from such analyses is then used to direct, optimize, and automate their decision making to successfully achieve their organizational goals. Data, text, and web mining technologies are some of the key contributors to making advanced analytics possible. This paper aims to investigate these three mining technologies in terms of how they are used and the issues that are related to their effective implementation and management within the broader context of predictive or advanced analytics. Design/methodology/approach -A range of recently published research literature on business intelligence (BI); predictive analytics; and data, text and web mining is reviewed to explore their current state, issues and challenges learned from their practice. Findings -The findings are reported in two parts. The first part discusses a framework for BI using the data, text, and web mining technologies for advanced analytics; and the second part identifies and discusses the opportunities and challenges the business managers dealing with these technologies face for gaining competitive advantages for their businesses. Originality/value -The study findings are intended to assist business managers to effectively understand the issues and emerging technologies behind advanced analytics implementation.

This article is directed towards information technology (IT) and marketing managers considering implementation of a customer relationship management (CRM) solution. The goal of this article is not to provide an all‐inclusive tutorial on CRM, but rather to provide a high level insight of the fundamental principles behind CRM and critical aspects of the IT development process. The article begins with an IT manager’s introduction into the basic CRM business and marketing principles. At the heart of the article is a proposed system development lifecycle that highlights the aspects unique or critical to CRM. Finally, it concludes with some final thoughts for long‐term success. After reading this article, the reader will be mindful of the major issues needed for success and be equipped to discuss primary development matters with vendors, staff and management.

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Over several years, there have been intensive discussions about the importance of knowledge management (KM) within the business community. Effectively implementing a sound KM strategy and becoming a knowledge-based company is seen as a mandatory condition of success for organizations as they enter the era of the knowledge economy. However, standardized metrics are needed to quantify knowledge and to fully convince management and stakeholders as to the value of KM initiatives. Development of KM metrics has begun in recent years and these metrics are being applied by some organizations, but more research is needed to better define these measures and to make them universal. The purpose of this research is to survey and report the current measures of knowledge assets or intellectual capital, as well as the methods that are popularly being followed by organizations to measure the performance of KM strategies. The research findings should: assist organizations in identifying the measures that are appropriate and suitable for them, for improving the quality of metrics they use for measuring KM effectiveness; and assist researchers in identifying future research needs toward the standardization of KM measurement metrics.

Given the important role being played by knowledge management (KM) systems in the current customer-centric business environment, there is a lack of a simple and overall framework to integrate the traditional customer relationship management (CRM) functionalities with the management and application of the customer-related knowledge, particularly in the context of marketing decisions. While KM systems manage an organization's knowledge through the process of creating, structuring, disseminating and applying knowledge to enhance organizational performance and create value, traditional CRM have focused on the transactional exchanges to manage customer interactions. True CRM is possible only by integrating them with KM systems to create knowledge-enabled CRM processes that allow companies to evaluate key business measures such as customer satisfaction, customer profitability, or customer loyalty to support their business decisions. Such systems will help marketers address customer needs based on what the marketers know about their customers, rather than on a mass generalization of the characteristics of customers. We address this issue in this paper by proposing an integrated framework for CRM through the application of knowledge management technology. The framework can be the basis for enhancing CRM development. Copyright # 2003 John Wiley & Sons, Ltd. INTRODUCTIONCRM is one of the hottest tools in business today. But like total quality management and reengineering before it, CRM has not always lived up to its hype (Brown, 2000;Swift, 2001). Still, companies ignore it at the risk of being left behind. Simply, CRM is a high-tech way of gathering mountains of information about customers, then using it to make customers happy-or at least a source of more business. It is therefore, concerned with understanding and influencing customer behavior (Kotler, 2000).One CRM trailblazer was the gaming company Harrah's Entertainment, which has successfully combined software and human marketing expertise to get gamblers into its 25 casinos. Harrah's do a thorough, sophisticated analysis of 24 million customers in their database. Harrah's know-how frequently customers come, what they play, and they then provide follow-up with continuous communication over the phone, direct mail and e-mail and on their Web site. It allows Harrah's to be participatory rather than being simply reactive. Their technologists refer to it as CRM but their managers refer it as their loyalty program.Although CRM is the fastest-growing business tool satisfaction with its use currently ranks quite low (Winer, 2001 (Zeithaml, 2001). CRM is not necessarily about automating or speeding up existing operational processes; rather, it is about developing and optimizing methodologies to intelligently manage customer relationships. Thus, it is about effectively managing and leveraging customer related information or knowledge, to better understand and serve customers.A true CRM solution design requires a complex combination of many best-of-breed components, including a...

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