A Roadmap to Evaluate Lean Six Sigma E-Health Reference Architectures Using a Fuzzy Group Bi-Objective LINMAP

Purpose: In recent years, although several studies have focused on Lean Six Sigma project selection, none of them have provided Lean Six Sigma approach to e-health reference architectures. Therefore, there is a significant gap of the application of the Lean Six Sigma in e-Health architectures in e-Health care quality improvement literature. In this paper, we present a Lean Six Sigma approach to e-health reference architectures to have high-quality healthcare in modern medicine. The purpose of this paper is to present a novel framework to present a roadmap to evaluate e-Health architectures from Lean and Six Sigma perspectives. Design/methodology/approach: At first, a novel model is presented to evaluate core e-Health modules and layers of e-Health reference architectures from a Six Sigma perspective. Then, the proposed model is used to evaluate core e-Health modules and layers of e-Health reference architectures from a Lean perspective. In order to overcome issues related to imprecise or vague judgments in, the proposed e-Health decision making model is presented in the fuzzy environment. Findings: Findings from this paper develop the LINMAP model to a Fuzzy Group bi-objective LINMAP to integrate Lean and Six Sigma perspectives and select the best practice Lean Six Sigma e-Health reference architecture

A Novel Fuzzy Group ANP Model for Global E-government Readiness Assessment from an e-Citizen Relationship Management Perspective

E-government readiness assessment is a significant indicator in measuring citizen satisfaction levels in using E-governmentservices. It provides an opportunity to learn about the government\u27s strengths and weakness on the journey to excellence.Simultaneously, the main goal of E-government is to create an optimized relationship with its citizens. This paper presents anE-Government readiness assessment framework for assessing services from an e-Citizen Relationship Management (e-CiRM)perspective using fuzzy Group Analytic Network Process (FGANP) and Technique for Order Preference by Similarity toIdeal Solution (TOPSIS) approaches. The proposed framework is applicable to assess E-government readiness as the processof government assessment irrespective of size and structure, and sector. The results of this Global assessment allowgovernments to discern clearly its strengths and areas in which improvement can be made regarding citizen\u27s needs

A strategic cooperative game-theoretic model for market segmentation with application to banking in emerging economies

Market segmentation is essential to target efficaciously core-segment customers and to obtain a competitive advantage. Firms when confronted by the range of market segments, have difficulty in deciding the core-segment customers who are the most probable purchasers of their product and services. We propose a novel fuzzy group multi-criteria method for market entry and segment evaluation and selection. This proposed method provides a comprehensive and systematic framework that combines bi-level multi-objective optimization with real option analysis (ROA) and fuzzy cooperative n-person game theory. The contribution of the proposed segment evaluation and selection method is fivefold: (1) it addresses the gaps in the marketing literature on the efficacious and effective assessment of market segments; (2) it provides a comprehensive and systematic framework that combines bi-level multi-objective optimization with ROA and fuzzy cooperative n-person game theory; (3) it considers fuzzy logic and fuzzy sets to represent ambiguous, uncertain or imprecise information; (4) it does not insist on consensus but synthesizes a representative outcome based on qualitative judgments and quantitative data; and (5) it is applicable to national and international market segmentation. The practical application of this proposed framework illustrates the efficacy of the procedures and algorithms

Applying fuzzy bi-dimensional scenario-based model to the assessment of Mars mission architecture scenarios

Sending man to Mars has been a long-held dream of humankind. NASA plans human planetary explorations using approaches that are technically feasible, have reasonable risks and have relatively low costs. This study presents a novel Multi-Attribute Decision Making (MADM) model for evaluating a range of potential mission scenarios for the human exploration of Mars. The three alternatives identified by the Mission Operations Directorate (MOD) at the Johnson Space Center (JSC) include split mission, combo lander and dual scenarios. The proposed framework subsumes the following key methods: first, the conjunction method is used to minimize the number of alternative mission scenarios; second, the Fuzzy Risk Failure Mode and Effects Analysis (RFMEA) is used to analyze the potential failure of the alternative scenarios; third, the fuzzy group Real Option Analysis (ROA) is used to estimate the expected costs and benefits of the alternative scenarios; and fourth, the fuzzy group permutation approach is used to select the optimal mission scenario. We present the results of a case study at NASA’s Johnson Space center to demonstrate: (1) the complexity of mission scenario selection involving subjective and objective judgments provided by multiple space exploration experts; and (2) a systematic and structured method for aggregating quantitative and qualitative data concerning a large number of competing and conflicting mission events

A fuzzy e-negotiation support system for inter-firm collaborative product development

Significant advances in manufacturing technology and the rapid intensification of the Internet and electronic commerce diffusion have given rise to competitive differentiation and rapid adaptability to competitive change. Newproduct development is a complex and collaborative process that requires negotiation and joint decision-making. We propose a fuzzy electronic negotiation (e-negotiation) support system based on cooperative multi-criteria game theory. The proposed system comprises three major processes: initialisation, e-negotiation and joint agreement. The Internet is used to facilitate the e-negotiation process and to minimise the response time in the decision-making process. The fuzzy sets are used to overcome issues related to the imprecise or vague judgments and incomplete information in the negotiation process. The proposed system enables the manufacturing parties involved in the negotiation process to determine the optimal coalition form for new product development and choose a common strategy to improve the payoffs of the members of the coalition group. Finally, a case study is used to demonstrate the applicability of the proposed framework and exhibit the efficacy of the procedures and algorithms in the mobile telecommunications industry

A Strategic Benchmarking Process for Identifying the Best Practice Collaborative Electronic Government Architecture

The rapid growth of the Internet has given rise to electronic government (e-government) which enhances communication, coordination, and collaboration between government, business partners, and citizens. An increasing number of national, state, and local government agencies are realizing the benefits of e-government. The transformation of policies, procedures, and people, which is the essence of e-government, cannot happen by accident. An e-government architecture is needed to structure the system, its functions, its processes, and the environment within which it will live. When confronted by the range of e-government architectures, government agencies struggle to identify the one most appropriate to their needs. This paper proposes a novel strategic benchmarking process utilizing the simple additive weighting method (SAW), real options analysis (ROA), and fuzzy sets to benchmark the best practice collaborative e-government architectures based on three perspectives: Government-to-Citizen (G2C), Government-to-Business (G2B), and Government-to-Government (G2G). The contribution of the proposed method is fourfold: (1) it addresses the gaps in the e-government literature on the effective and efficient assessment of the e-government architectures; (2) it provides a comprehensive and systematic framework that combines ROA with SAW; (3) it considers fuzzy logic and fuzzy sets to represent ambiguous, uncertain or imprecise information; and (4) it is applicable to international, national, Regional, state/provincial, and local e-government levels

An optimisation model for traffic distribution forecasting in packet-switching networks

Traffic distribution forecasting is an essential step in network planning for packet-switching networks. It is frequently necessary to forecast and develop an optimal network configuration to meet the requirements of new traffic demands or changes in the existing demands. Several methods have been developed to forecast network configurations. While these studies have revealed some interesting traffic characteristics, little progress has been made in developing good models for the purpose of traffic engineering and performance prediction. We propose a novel multi-objective optimisation model for traffic distribution forecasting in packet-switching networks by mapping these networks into multi-commodity networks. Initially, the radial basis function (RBF) network is used to monitor and learn the current real-traffic distribution. Next, a quadratic model is used to calibrate these functions for a precise traffic distribution. The proposed multi-objective optimisation method can effectively and efficiently forecast the traffic distribution of packet-switching networks in both crisp and fuzzy environments. A numerical example is presented to demonstrate the application and effectiveness of this model

A hybrid fuzzy real option analysis and group ordinal approach for knowledge management strategy assessment

The intensity of global competition and ever-increasing economic uncertainties has led organizations to search for more efficient and effective ways to improve organizational productivity by investing in knowledge management (KM) initiatives. In this research, we propose a framework to assess KM investment opportunities. Precise and crisp information is fundamentally indispensable in strategic investment assessment. However, the information concerning future investment opportunities in the real world is often imprecise or ambiguous. Initially, fuzzy real option valuation is used to estimate the value of the KM strategies. Next, a multi-criteria decision-making model is proposed to determine the optimal KM strategy in deferral time. Then, a group ordinal approach is used to capture and quantify the underlying uncertainties in the valuating process. Finally, the optimal KM strategy and the best time to implement this strategy is determined by a novel objective decision-making model. The contribution of this paper is fourfold: (1) it addresses the gaps in KM literature on the effective and efficient assessment of KM investment opportunities; (2) it provides a comprehensive and systematic framework that combines real option analysis with a group ordinal approach to assess KM investment strategies; (3) it considers fuzzy logic and fuzzy sets to represent ambiguous, uncertain or imprecise information; and (4) it uses a real-world case study to demonstrate the applicability of the proposed framework and exhibit the efficacy of the procedures and algorithms

A fuzzy goal programming model for strategic information technology investment assessment

Purpose: The high expenditures in information technology (IT) and the growing usage that penetrates the core of business have resulted in a need to effectively and efficiently evaluate strategic IT investments in organizations. The purpose of this paper is to propose a novel two‐dimensional approach that determines the deferrable strategy with the most value by maximizing the real option values while minimizing the risks associated with each alternative strategy. Design/methodology/approach: In the proposed approach, first, the deferrable investment strategies are prioritized according to their values using real option analysis (ROA). Then, the risks associated with each investment strategy are quantified using the group fuzzy analytic hierarchy process. Finally, the values associated with the two dimensions are integrated to determine the deferrable IT investment strategy with the most value using a fuzzy preemptive goal programming model. Findings: Managers face the difficulty that most IT investment projects are inherently risky, especially in a rapidly changing business environment. The paper proposes a framework that can be used to evaluate IT investments based on the real option concept. This simple, intuitive, generic and comprehensive approach incorporates the linkage among economic value, real option value and IT investments that could lead to a better‐structured decision process. Originality/value: In contrast to the traditional ROA literature, the approach contributes to the literature by incorporating a risk dimension parameter. The paper emphasizes the importance of categorizing risk management in IT investment projects since some risk cannot be eliminated

An Optimal Investment Scheduling Framework for Intelligent Transportation Systems Architecture

Transportation planning in general, and planning for intelligent transportation systems (ITSs) in particular, are notable for multiple goals and for multiple constituencies. A review of the current literature offers several ITS investment evaluation methods that provide frameworks for the quantification of risks and benefits. Nevertheless, the traditional selection methods overemphasize quantitative and economic analysis and often neglect to consider qualitative and noneconomic data in the formal selection process. Furthermore, crisp data are fundamentally indispensable in traditional ITS investment selection methods. However, the data in real-world problems are often imprecise or ambiguous. In this article, we propose a novel fuzzy group multi-criteria framework for ITS investment evaluation and selection that takes into consideration (1) the qualitative and quantitative criteria and their respective value judgments; (2) the verbal expressions and linguistic variables for qualitative judgments which lead to ambiguity in the decision process; and (3) imprecise or vague judgments. First, we use fuzzy TOPSIS to calculate the fuzzy risk values with each ITS architecture subsystem. Next, we use fuzzy ROA to calculate the fuzzy real option values of the ITS subsystems. Last, we determine the optimal investment schedule for the ITS subsystems by considering the risk and option values as the coefficients of the objective functions in a group multi-objective decision-making model