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To provide an interesting approach for determining interval measures, through the analytic hierarchy process, for integration with social network analysis for knowledge mapping in organizations.

In order to develop improved organizational and business processes through knowledge management, a knowledge audit should be conducted to better understand the knowledge flows in the organization. An important technique to visualize these knowledge flows is the use of a knowledge map. Social network analysis can be applied to develop this knowledge map. Interval measures should be used in the social network analysis in order to determine the strength of the connections between individuals or departments in the organization. This paper applies the analytic hierarchy process to develop these interval measures, and integrates the values within the social network analysis to produce a meaningful knowledge map.

The analytic hierarchy process, when coupled with social network analysis, can be a useful technique for developing interval measures for knowledge‐mapping purposes.

The analytic hierarchy process may become tedious and arduous for use in large social network maps. More research needs to be conducted in this area for scalability.

As social network analysis is gaining more prominence in the knowledge management community, the analytic hierarchy process may be able to provide more valuable measures to determine the strengths of relationships between actors than simply using ordinal numbers.

Coupling the analytic hierarchy process with social network analysis provides a novel approach for future knowledge‐mapping activities.

The high‐tech industry is the economic lifeline for Taiwan. Its characteristics are short product life cycle, rapid changes in the market, and a high obsolescence rate for new products. Under globalization, the high‐tech industry has adopted Information Technology (IT) to shorten the manufacturing process, reduce costs and conduct product research and development (R&D) to increase the core competence of enterprises and achieve the goal of sustainable operations. Enterprises should actively strengthen their integration with internal and external resources and lead in R&D management to increase industrial operating performance. Effectively managing operations and R&D management evaluation in Taiwan’s High‐tech Industry has become a critical subject. This study adopted 4 major Balanced Scorecard (BSC) perspectives to establish the Total Performance Evaluation Indicators for the R&D management department in Taiwan’s High‐tech Industry. The Analytic Network Process (ANP) was applied to evaluate the overall performance of the R&D management department. The research framework is divided into 2 phases. The first phase is combined with the 4 major perspectives, Financial, Customer, Internal Business Process and Learning and Growth, as the related indicators for each measurement perspective. The Key Performance Indicators (KPI) were selected using Factor Analysis to identify the key factor from the complicated indicators. The relationship between the characteristics of each BSC’s evaluation perspective is dependence and feedback. This study applied ANP to conduct the calculation and adjustment of correlation between each KPI, and determine on their relative weights for the objective KPI. The “Financial Perspective” for R&D management department in Taiwan’s High‐tech Industry focused on the budget achievement rate of R&D management. The weight indicator value is (0.05863). The “Customer Perspective” focused on problem‐solving satisfaction. The weight value of this indicator is (0.17549). The “Internal Business Process Perspective” focused on the quantity and quality of R&D. The weight value of this indicator is (0.13506). The “Learning and Growth Perspective” focused on improving competence in the research ersonnel’s professional techniques. The weight value of this indicator is (0.02789). From the total weighting indicators, the order of the Performance Indicators for the R&D management department in Taiwan’s High‐tech Industry is: (1) Customer Perspective; (2) Internal Business Process Perspective; (3) Financial Perspective; and (4) Learning and Growth Perspective.

High‐tech industry has been the principal economic source for Taiwan in recent years. The characteristics of high‐tech industries in Taiwan are changeable product markets, short product life cycles and high company attrition rate. In the globalization trend, the high‐tech industry has gradually increased corporate competitiveness and reached the goal of sustainable operations through knowledge management, knowledge sharing and new product research and development. Firms have aggressively strengthened and integrated their internal and external resources and enhanced knowledge sharing to increase industry operational performance. Effectively strengthening the knowledge management operation and performance evaluation of knowledge sharing in Taiwan’s high‐tech industry has become a critical issue. In the selection of knowledge sharing Key Performance Indicators (KPI), this research divided the knowledge sharing indicators into representative strategic indicators such as organizational knowledge learning, organizational knowledge resources, organizational information capacity and organizational knowledge performance through screening using Factor Analysis. The characteristics of the constructs were interdependent. This research calculated and adjusted the correlation among the key performance knowledge sharing indicators using ANP and determined the relative weight of knowledge sharing.

Lean manufacturing (LM) is prevalent in the manufacturing industry; thus, focusing on fast and accurate lean tool implementation is the new paradigm in manufacturing. Value stream mapping (VSM) is one of the many LM tools. It is understood that combining LM implementation with VSM tools can generate better outcomes. This paper aims to develop an expert system for optimal sequencing of VSM tools for lean implementation.

A proposed artificial neural network (ANN) model is based on the analytic network process (ANP) devised for this study. It will facilitate the selection of VSM tools in an optimal sequence.

Considering different types of wastes and their level of occurrence, organizations need a set of specific tools that will be effective in the elimination of these wastes. The developed ANP model computes a level of interrelation between wastes and VSM tools. The ANN is designed and trained by data obtained from numerous case studies, so it can predict the accurate sequence of VSM tools for any new case data set.

The design and use of the ANN model provide an integrated result of both empirical and practical cases, which is more accurate because all viable aspects are then considered. The proposed modeling approach is validated through implementation in an automobile manufacturing company. It has resulted in benefits, namely, reduction in bias, time required, effort required and complexity of the decision process. More importantly, according to all performance criteria and subcriteria, the main goal of this research was satisfied by increasing the accuracy of selecting the appropriate VSM tools and their optimal sequence for lean implementation.

There has been an increasing amount of research on personnel selection in many business disciplines (Hough & Oswald, 2000; Breaugh & Starke, 2000). Research on internal auditor selection, however, has had limited exposure in the auditing literature (Bailey, Gramling, & Ramamoorti, 2003). Recently, Seol and Sarkis (2005) introduced an analytic hierarchy process (AHP) model that used a decision hierarchy based on the CFIA (competency framework for internal auditing) framework. A limitation of AHP, however, is the assumption of strict hierarchical relationship that needs to exist among factors.

The purpose of this paper is an introduction of a more robust model, the analytical network process (ANP), which relaxes the strict hierarchical and decomposition levels of the hierarchy and incorporates possible interrelationships and interdependencies of various personnel selection criteria, factors, and alternatives. In illustrating the application, we return to the CFIA model framework, describe how and where interdependencies exist amongst the CFIA factors/attributes, and how ANP is used in the internal auditor selection process. The illustration will also describe some sensitivity analysis for the ANP approach. The tool is not without its limitations that include the potential for geometrically more questions and information elicitation from the decision makers. Finally managerial and research implications associated with the technique and results are described.

This study integrates economic/ecology (eco)-attributes and performance to build a sustainable service supply chain management (SSCM) model.

This study proposes the use of the fuzzy Delphi method to screen for the less important attributes and applies a network data envelopment analysis to explore the hierarchical and eco-efficient network interrelationships. The causality and hierarchal eco-efficient model is acquired using a fuzzy decision-making trial and evaluation laboratory analysis

The findings are as follows: (1) the information and technology management process is derived by enhancing sustainable customer and supplier relationship management, and (2) the eco-efficient model is improved based on long-term relationships with suppliers – that is, synergistic suppliers improve the service chain quality and provide services in an appropriate and timely manner – and research and development coordination. The theoretical and managerial implications are discussed.

The eco-efficient model reveals that the sustainable customer relationship management process, sustainable supplier relationship management process and information and technology management process are the major causal attributes in the model.

The eco-efficient model must be based on (1) long-term relationships with suppliers, (2) synergistic suppliers to improve service chain quality, (3) the provision of services in a timely manner and (4) research and development coordination.

Prior studies neglect to build an ecological economy model using the efficiency causality model of hierarchical interrelationships. Traditional SSCM fails to involve the triple bottom line performance toward sustainability.

To strengthen the correlation analysis on risk factors of drug production safety and reduce the influence due to fuzzy judgments, a safety risk assessment method based on Grey-Analytic Network Process (G-ANP) is proposed.

First, an index system evaluating drug production safety risk is constructed according to the “Good Manufacture Practice of Medical Products,” next the influence weight of each risk index is derived by using the Analytic Network Process, then the grey number of each risk index is determined by further utilizing the grey statistical theory, and finally the risk level of drug production is obtained.

An empirical study is conducted and the results support the feasibility and practicability to use G-ANP method for drug production safety risk evaluation. The results of the case show that it is feasible and practical to use G-ANP method for drug production safety risk evaluation.

The innovation lies in the use of G-ANP method to fully consider the interdependence and interaction between the risk factors of drug production safety, which improves the objectivity in judging the risk level of drug production and provides a scientific basis for pharmaceutical manufacturers to formulate further decisions and management in the case of insufficient quantification of risk factors. Based on the findings, more targeted suggestions are made to reduce the production risk of pharmaceutical enterprises.

This study develops a model for selecting Internet advertising networks. The proposed model adopts the “analytic hierarchy process” (AHP) to determine the relative weights of evaluative criteria, then ranks the alternatives and selects the optimum Internet advertising network for advertisers. Additionally, a famous Taiwanese food company is used herein as an example of how an Internet advertising network can be selected using this model. The proposed model helps advertisers to effectively select Internet advertising networks, making it highly applicable for academia and commerce.

This paper presents the employment of the analytic network process (ANP) to select the best site for a shopping mall. ANP is an innovative and robust multicriteria decision‐making (MCDM) method because it can produce a comprehensive analytic framework for solving societal, governmental, and corporate decision problems. Yet, there is a lack of published papers in the construction field demonstrating the method with illustrative examples. In the current paper, it is suggested that ANP is appropriate for shopping mall location selection. An example is therefore demonstrated. In order to explicate the difference between ANP and analytic hierarchy process (AHP), the findings obtained from the two methods are compared. Results of the comparison indicate that ANP is a powerful tool to solve the decision problem if interdependent relationships have substantial impacts in the decision model.

The aim of this research is to provide an approach for modeling system risk management and to develop an analytic hierarchy process (AHP)-based model for simulating decisions on introducing innovations in air transport systems.

The paper proposes AHP and analytic network process (ANP) methodologies for overcoming fragmentation in risk assessments perceived by risk, budget, quality or schedule managements, and for resolving potential conflicts between safety, efficiency and well-being.

Issues in system risk evaluation and management were identified and transferred to a list of requirements. A generic ANP-based model for system risk management was developed as well as a template for capture of knowledge on risks, including expert knowledge, and for implementation of a new decision-making process as applied to introducing innovation(s).

Since this research addresses evaluation and management of non-event based risks due to innovations in air transport systems, further analysis and re-evaluation of risks is required during and after the implementation in order to provide continuously dynamic representation of system risk.

The results of this study contribute to the development and implementation of a usable version of multi-criteria decision analysis at senior management level. Further, it stimulates mechanism for learning and trade-offs between various stakeholders.

This work is original in that it is cross-disciplinary (e.g. risk management, management of innovation, systems design). It addresses the issue of integrating a safety management system with an overall business management system. Also, it introduces qualitative non-event risk assessments into system risk management. In addition to the use of the AHP-model for system risk management, an implementation model (“risk stakeholder model”) is also developed.