Enterprise Resource Planning (ERP)

Business needs have driven the design, development, and use of Enterprise Resource Planning (ERP) systems. Intra-enterprise integration was a driving force in the design, development, and use of early ERP systems, but increased globalization, intense competition, and technological change have shifted to focus to inter-enterprise integration. Current and evolving ERP systems thus reflect the expanded scope of integration, with greater emphasis on things like supply chain management and customer relationship management. This manuscript explores the evolution of ERP, the current status of ERP, and the future of ERP, with the objective of promoting relevant future research in this important area. If researchers hope to play a significant role in the design, development, and use of suitable ERP systems to meet evolving business needs, then their research should focus, at least in part, on the changing business environment, its impact on business needs, and the requirements for enterprise systems that meet those needs.

Customer Relationship Management (CRM) Metrics

Adopting a focus on CRM has been an industry standard for nearly two decades. While evidence suggests that a majority of the attempts to implement CRM systems fail, no single reason for the failures has been identified. Assuming that CRM implementation is an extension of a customeroriented business strategy and assuming successful integration with Enterprise Information Systems such as Enterprise Resource Planning (ERP) systems, the authors contend that the lack of valid and reliable CRM metrics leads to the perception of failed CRM implementation. Only through the development, application, and use of CRM metrics can organizations hope to achieve their CRM goals.

Information System Development Failure and Complexity

This chapter examines the causes of failure in a Web-based information system development project and finds out how complexity can lead a project towards failure. Learning from an Information System Development Project (ISDP) failure plays a key role in the long-term success of any organization desirous of continuous improvement via evaluation and monitoring of its information systems (IS) development efforts. This study reports on a seemingly simple (but only deceptively so) failed ISDP to inform the reader about the various complexities involved in ISDPs in general, and in developing countries in particular. An existing framework from contemporary research is adopted to map the complexities found in the project under study and the critical areas, which lead to the decreased reliability and failure in Web-based information system development, are highlighted.

The Cognitive Process of Decision Making

Decision making is one of the basic cognitive processes of human behaviors by which a preferred option or a course of actions is chosen from among a set of alternatives based on certain criteria. Decision theories are widely applied in many disciplines encompassing cognitive informatics, computer science, management science, economics, sociology, psychology, political science, and statistics. A number of decision strategies have been proposed from different angles and application domains such as the maximum expected utility and Bayesian method. However, there is still a lack of a fundamental and mathematical decision model and a rigorous cognitive process for decision making. This article presents a fundamental cognitive decision making process and its mathematical model, which is described as a sequence of Cartesian-product based selections. A rigorous description of the decision process in real-time process algebra (RTPA) is provided. Real-world decisions are perceived as a repetitive application of the fundamental cognitive process. The result shows that all categories of decision strategies fit in the formally described decision process. The cognitive process of decision making may be applied in a wide range of decision-based systems such as cognitive informatics, software agent systems, expert systems, and decision support systems.

Making Decisions with Data

This chapter identifies important barriers to the successful application of Computational Intelligence (CI) techniques in a commercial environment and suggests a number of ways in which they may be overcome. It identifies key conceptual, cultural and technical barriers and describes the different ways in which they affect both the business user and the CI practitioner. The chapter does not provide technical detail on how to implement any given technique, rather it discusses the practical consequences for the business user of issues such as non-linearity and extrapolation. For the CI practitioner, we discuss several cultural issues that need to be addressed when seeking to find a commercial application for CI techniques. The authors aim to highlight to technical and business readers how their different expectations can affect the successful outcome of a CI project. The authors hope that by enabling both parties to understand each other’s perspective, the true potential of CI can be realized.

Implementing Supply Chain Management in the New Era

Combining with the collaborations between business customers and suppliers, traditional purchasing and logistics functions have evolved into a broader concept of materials and distribution management, namely, supply chain management (SCM) (Tan, 2001). This chapter reviews the literature of SCM from several paths that can be the basis of a proposed framework for SCM within academic and managerial contexts. In addition, it includes the approaches of supply chain operations reference (SCOR) model, which was developed by the Supply Chain Council and is recognised as a diagnostic tool for SCM worldwide. This chapter also summarises the literature of performance control and risk issues in SCM and the SCOR Model and discusses a proposed framework for the future research.

The Nature of Strategic Intelligence

This chapter discusses the nature of strategic intelligence and the challenges of systematically scanning and processing strategic information. It reveals that strategic intelligence practice concentrates on competitive intelligence gathering, non-competitive related intelligence have not yet been systematically scanned and processed. Much of the intelligence is collected through informal and manual based systems. Turning data into analyzed, meaningful intelligence for action is limited to a few industry leaders. The chapter proposed a corporate intelligence solution, which comprises of three key intelligence functions, namely organizational-wide intelligence scanning, knowledge enriched intelligent refining, and specialist support. A corporate radar system (CRS) for external environment scanning, which is a part of the organizational-wide intelligence scanning process is explored in light of latest technology development. Implementation issues are discussed. The chapter develops insight of strategic intelligence, and the solution could significantly enhance a manager’s and a company’s sensibility and capability in dealing with external opportunities and threats.

The Future of Supply Chain Management

This chapter initiates the concept of a customercentric model in supply chain systems. It discusses various constraints of present-day supply chain systems resulting from their roots being in logistics management and suggests an alternative next-level paradigm of a customer-centric matrix model. This chapter further demonstrates how this model would add value to the customer by taking the example of a healthcare information management system. The chapter also delves into the limitations of and anticipated issues and challenges in implementing the suggested model. Finally, the chapter hints at some broad directions for future research and action in the field. Emergent behavior is what happens when an interconnected system of relatively simple elements begins to self-organize to form a more intelligent and more adaptive higher-level system (Johnson, 2001).

An Application of Multi-Criteria Decision-Making Model to Strategic Outsourcing for Effective Supply-Chain Linkages

An appropriate outsourcing and supply-chain planning strategy needs to be based on compromise and more objective decision-making procedures. Although factors affecting business performance in manufacturing firms have been explored in the past, focuses are on financial performance and measurement, neglecting intangible and nonfinancial factors in the decision-making planning process. This study presents development of an integrated multi-criteria decision-making (MCDM) model. This model aids in allocating outsourcing and supply-chain resources pertinent to strategic planning by providing a satisfying solution. The model was developed based on the data obtained from a business firm producing intelligent home system devices. This developed model will reinforce a firm’s ongoing outsourcing strategies to meet defined requirements while positioning the supply-chain system to respond to a new growth and innovation.

EBBSC

E-business is far more about strategy than technology, and the strategy of e-business is very important in today’s dynamic and competitive environment. In this article, we describe a balanced scorecard-based framework in detail and discuss its potential e-business uses. This framework enables e-business managers to plan and allocate resources more effectively and align strategic objectives with performance results. It also provides a stable point of reference for e-businesses to understand and manage the fundamental changes introduced by e-business initiatives.