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Objectives This study aims to identify significant symptoms and non-symptom-related factors for malaria diagnosis in endemic regions of Indonesia. Methods Medical records are collected from patients suffering from malaria and other febrile diseases from public hospitals in endemic regions of Indonesia. Interviews with eight Indonesian medical doctors are conducted. Feature selection and machine learning techniques are used to develop malaria classifiers for identifying significant symptoms and non-symptom-related factors. Results Seven significant symptoms (duration of fever, headache, nausea and vomiting, heartburn, severe symptom, dizziness and joint pain) and patients' history of malaria as a non-symptom-related factor contribute most to malaria diagnosis. As a symptom, fever duration is more significant than temperature or fever for distinguishing malaria from other febrile diseases. Shivering, fever and sweating (known to indicate malaria presence in Indonesia) are shown to be less significant than other symptoms in endemic regions. Conclusions Three most suitable malaria classifiers have been developed to identify significant features that can be used to predict malaria as distinct from other febrile diseases. With extensive experiments on the classifiers, the significant features identified can help medical doctors in the clinical diagnosis of malaria and raise public awareness of significant malaria symptoms at early stages.
Yulianti Paula Bria; Chung-Hsing Yeh; Susan Bedingfield. Significant symptoms and nonsymptom-related factors for malaria diagnosis in endemic regions of Indonesia. International Journal of Infectious Diseases 2020, 103, 194 -200.
AMA StyleYulianti Paula Bria, Chung-Hsing Yeh, Susan Bedingfield. Significant symptoms and nonsymptom-related factors for malaria diagnosis in endemic regions of Indonesia. International Journal of Infectious Diseases. 2020; 103 ():194-200.
Chicago/Turabian StyleYulianti Paula Bria; Chung-Hsing Yeh; Susan Bedingfield. 2020. "Significant symptoms and nonsymptom-related factors for malaria diagnosis in endemic regions of Indonesia." International Journal of Infectious Diseases 103, no. : 194-200.
Renewable energy (RE) microgrids are considered one solution for solving the increasing electricity demand and environmental pollution problem. Selecting RE sources for a microgrid plays a crucial role in determining the performance of the microgrid. Illustrated with an empirical study on a city’s microgrid project, this paper proposes a new evaluation approach with a bi-capacity based multi-criteria decision making method called Bi-ELECTRE to evaluate and select RE source alternatives based on interacting performance indicators with bipolar measurement. With the novelty of the Bi-ELECTRE method, this paper addresses the questions of (a) how to measure interactions between bipolar-scaled indicators when evaluating the RE source alternatives of a microgrid, and (b) how to determine the optimal combination of RE sources for a microgrid. The results from the empirical study suggest that a microgrid with a single RE source has the worst performance, compared with multi-source alternatives. In the empirical study conducted, the microgrid using a RE source combination of 20 biomass has the best overall performance. By considering interactions between bipolar-scaled indicators and various combinations of RE sources, the proposed approach contributes to MCDM research methodologically and to the RE source selection problem for a microgrid practically.
Ling Zhang; Fandi Wang; Yan Xu; Chung-Hsing Yeh; Peng Zhou. Evaluating and Selecting Renewable Energy Sources for a Microgrid: A Bi-Capacity-Based Multi-Criteria Decision Making Approach. IEEE Transactions on Smart Grid 2020, 12, 921 -931.
AMA StyleLing Zhang, Fandi Wang, Yan Xu, Chung-Hsing Yeh, Peng Zhou. Evaluating and Selecting Renewable Energy Sources for a Microgrid: A Bi-Capacity-Based Multi-Criteria Decision Making Approach. IEEE Transactions on Smart Grid. 2020; 12 (2):921-931.
Chicago/Turabian StyleLing Zhang; Fandi Wang; Yan Xu; Chung-Hsing Yeh; Peng Zhou. 2020. "Evaluating and Selecting Renewable Energy Sources for a Microgrid: A Bi-Capacity-Based Multi-Criteria Decision Making Approach." IEEE Transactions on Smart Grid 12, no. 2: 921-931.
Most existing object detection models are restricted to detecting objects from previously seen categories, an approach that tends to become infeasible for rare or novel concepts. Accordingly, in this paper, we explore object detection in the context of zero-shot learning, i.e., Zero-Shot Object Detection (ZSD), to concurrently recognize and localize objects from novel concepts. Existing ZSD algorithms are typically based on a simple mapping-transfer strategy that is susceptible to the domain shift problem. To resolve this problem, we propose a novel Semantics-Preserving Graph Propagation model for ZSD based on Graph Convolutional Networks (GCN). More specifically, we employ a graph construction module to flexibly build category graphs by incorporating diverse correlations between category nodes; this is followed by two semantics preserving modules that enhance both category and region representations through a multi-step graph propagation process. Compared to existing mapping-transfer based methods, both the semantic description and semantic structural knowledge exhibited in prior category graphs can be effectively leveraged to boost the generalization capability of the learned projection function via knowledge transfer, thereby providing a solution to the domain shift problem. Experiments on existing seen/unseen splits of three popular object detection datasets demonstrate that the proposed approach performs favorably against state-of-the-art ZSD methods.
Caixia Yan; Qinghua Zheng; Xiaojun Chang; Minnan Luo; Chung-Hsing Yeh; Alexander G. Hauptmann. Semantics-Preserving Graph Propagation for Zero-Shot Object Detection. IEEE Transactions on Image Processing 2020, 29, 8163 -8176.
AMA StyleCaixia Yan, Qinghua Zheng, Xiaojun Chang, Minnan Luo, Chung-Hsing Yeh, Alexander G. Hauptmann. Semantics-Preserving Graph Propagation for Zero-Shot Object Detection. IEEE Transactions on Image Processing. 2020; 29 (99):8163-8176.
Chicago/Turabian StyleCaixia Yan; Qinghua Zheng; Xiaojun Chang; Minnan Luo; Chung-Hsing Yeh; Alexander G. Hauptmann. 2020. "Semantics-Preserving Graph Propagation for Zero-Shot Object Detection." IEEE Transactions on Image Processing 29, no. 99: 8163-8176.
E-waste, also known as waste electrical and electronic equipment, has become one of the fastest growing waste streams worldwide. As the world’s largest e-waste processing country, China’s e-waste management practice is facing multiple barriers to meet the requirement of sustainability from the economic, environmental and social perspectives. With an empirical study on the e-waste management practice of a major province in Western China, this paper develops an integrated planning approach for evaluating and managing the barriers which have mutual influence on their impact on the e-waste management practice. In consideration of interactive relationships of the barriers, a barrier assessment process is developed to assess the direct and indirect impacts of the barriers on the sustainable e-waste management practice in terms of economic, environmental and social sustainability criteria. A strategic planning process is proposed to categorise the barriers into four planning zones based on their overall impact and mitigation level. This paper contributes to e-waste management research by providing a structured approach for managing interactive barriers to achieve sustainable e-waste management. The proposed approach represents a methodological contribution to multicriteria evaluation research involving sustainability criteria and interactive alternatives.
Yan Xu; Chung-Hsing Yeh; Chenguang Liu; Sidra Ramzan; Ling Zhang. Evaluating and managing interactive barriers for sustainable e-waste management in China. Journal of the Operational Research Society 2020, 1 -14.
AMA StyleYan Xu, Chung-Hsing Yeh, Chenguang Liu, Sidra Ramzan, Ling Zhang. Evaluating and managing interactive barriers for sustainable e-waste management in China. Journal of the Operational Research Society. 2020; ():1-14.
Chicago/Turabian StyleYan Xu; Chung-Hsing Yeh; Chenguang Liu; Sidra Ramzan; Ling Zhang. 2020. "Evaluating and managing interactive barriers for sustainable e-waste management in China." Journal of the Operational Research Society , no. : 1-14.
Recycling companies need to implement strategies to improve their current e-waste management practice for achieving sustainability. With the innovative nature of the improvement strategies and the uncertainty of operational settings, a variety of risks are inevitably associated with their implementation. These risks are interrelated and may affect the performance of these strategies. Different from existing multi-criteria decision making (MCDM)-based evaluation and risk assessment methods, this paper proposes a new risk-based performance evaluation approach for evaluating the e-waste management improvement strategies. The novelty of the proposed approach lies in the fact that it incorporates the impact of interrelated risks of various types on the sustainability performance of strategies by considering the probability of occurrence and the severity of consequence of risks. An empirical study on an e-waste recycling company in China is conducted to illustrate the effectiveness of the approach. The evaluation outcome provides the case company with useful new insights in managing the improvement strategies and their potential risks as a whole and individually. A value-risk matrix analysis is conducted to help the case company direct its management efforts and resources when implementing the improvement strategies under risks. The approach makes methodological and practical contributions to MCDM research and e-waste management practice.
Yan Xu; Chung-Hsing Yeh; Shaopeng Yang; Bhumika Gupta. Risk-based performance evaluation of improvement strategies for sustainable e-waste management. Resources, Conservation and Recycling 2020, 155, 104664 .
AMA StyleYan Xu, Chung-Hsing Yeh, Shaopeng Yang, Bhumika Gupta. Risk-based performance evaluation of improvement strategies for sustainable e-waste management. Resources, Conservation and Recycling. 2020; 155 ():104664.
Chicago/Turabian StyleYan Xu; Chung-Hsing Yeh; Shaopeng Yang; Bhumika Gupta. 2020. "Risk-based performance evaluation of improvement strategies for sustainable e-waste management." Resources, Conservation and Recycling 155, no. : 104664.
Various imputation approaches have been proposed to address the issue of missing values in data mining and machine learning applications. To improve the accuracy of missing data imputation, this paper proposes a new method called DIFC by integrating the merits of decision tress and fuzzy clustering into an iterative learning approach. To compare the performance of the DIFC method against five effective imputation methods, extensive experiments are conducted on six widely used datasets with numerical and categorical missing data, and with various amounts and types of missing values. The experimental results show that the DIFC method outperforms other methods in terms of imputation accuracy. Further experiments on the effect of missing value types demonstrate the robustness of the DIFC method in dealing with different types of missing values. This paper contributes to missing data imputation research by providing an accurate and robust method.
Sanaz Nikfalazar; Chung-Hsing Yeh; Susan Bedingfield; Hadi A. Khorshidi. Missing data imputation using decision trees and fuzzy clustering with iterative learning. Knowledge and Information Systems 2019, 62, 2419 -2437.
AMA StyleSanaz Nikfalazar, Chung-Hsing Yeh, Susan Bedingfield, Hadi A. Khorshidi. Missing data imputation using decision trees and fuzzy clustering with iterative learning. Knowledge and Information Systems. 2019; 62 (6):2419-2437.
Chicago/Turabian StyleSanaz Nikfalazar; Chung-Hsing Yeh; Susan Bedingfield; Hadi A. Khorshidi. 2019. "Missing data imputation using decision trees and fuzzy clustering with iterative learning." Knowledge and Information Systems 62, no. 6: 2419-2437.
The evaluation of urban land use efficiency (ULUE) plays an important role in achieving the sustainable use of land resources. Illustrated with an empirical study on the evaluation of ULUE of 13 cities in Jiangsu, China, this paper develops an efficiency evaluation approach for measuring the ULUE with respect to interacting sustainability-related criteria, using bipolar measurement. The approach incorporates the merits of the decision-making trial and evaluation laboratory method, a new causal-effect analysis process, the Bi-TOPSIS method, and convergence models. As such, this paper addresses three important issues: (a) how to identify key criteria and their interactions for evaluating the ULUE of cities; (b) how to obtain the ULUE performances of cities, with benchmarks that clearly demarcate ‘satisfactory’ from ‘unsatisfactory’ performances, and (c) how to measure the dispersion of the ULUE performances across cities over time. The results from the empirical study suggest that the ULUE of most Jiangsu cities is below the city planner’s expectation. The ULUE of Central Jiangsu cities is better than their neighboring cities, and the cities with low ULUE tend to catch up with higher ULUE cities. However, the gaps between their ULUE performances will still exist. Each city’s ULUE performance can only converge to its own steady state over time. To help cities achieve a better ULUE performance, policy suggestions are recommended.
Ling Zhang; Lei Zhang; Yan Xu; Peng Zhou; Chung-Hsing Yeh. Evaluating urban land use efficiency with interacting criteria: An empirical study of cities in Jiangsu China. Land Use Policy 2019, 90, 104292 .
AMA StyleLing Zhang, Lei Zhang, Yan Xu, Peng Zhou, Chung-Hsing Yeh. Evaluating urban land use efficiency with interacting criteria: An empirical study of cities in Jiangsu China. Land Use Policy. 2019; 90 ():104292.
Chicago/Turabian StyleLing Zhang; Lei Zhang; Yan Xu; Peng Zhou; Chung-Hsing Yeh. 2019. "Evaluating urban land use efficiency with interacting criteria: An empirical study of cities in Jiangsu China." Land Use Policy 90, no. : 104292.
Existing approaches to Chinese semantic role labeling (SRL) mainly adopt deep long short-term memory (LSTM) neural networks to address the long-term dependencies problem. However, deep LSTM networks cannot address the vanishing gradient problem properly. In addition, the complexity of the Chinese language, as a hieroglyphic language, decreases the performance of traditional SRL approaches to Chinese SRL. To address these problems, this paper proposes a new approach with a deep bidirectional highway LSTM network. The performance of the proposed approach is further improved by introducing the conditional random fields (CRFs) constraints and part-of-speech (POS) feature since POS tags are the classes of formal equivalents of words in linguistics. The experimental results on the commonly used Chinese Proposition Bank dataset show that the proposed approach outperforms existing approaches. With an easily acquired and reliable POS feature for practical applications, the proposed approach substantially improves Chinese SRL.
Qi Xia; Chung-Hsing Yeh; Xiang-Yu Chen. A Deep Bidirectional Highway Long Short-Term Memory Network Approach to Chinese Semantic Role Labeling. 2019 International Joint Conference on Neural Networks (IJCNN) 2019, 1 -6.
AMA StyleQi Xia, Chung-Hsing Yeh, Xiang-Yu Chen. A Deep Bidirectional Highway Long Short-Term Memory Network Approach to Chinese Semantic Role Labeling. 2019 International Joint Conference on Neural Networks (IJCNN). 2019; ():1-6.
Chicago/Turabian StyleQi Xia; Chung-Hsing Yeh; Xiang-Yu Chen. 2019. "A Deep Bidirectional Highway Long Short-Term Memory Network Approach to Chinese Semantic Role Labeling." 2019 International Joint Conference on Neural Networks (IJCNN) , no. : 1-6.
An effective missing data imputation method is essential for data mining and knowledge discovery from a comprehensive database with missing values. This paper proposes a new hybrid imputation method to effectively deal with the missing data issue of the Mobility in Cities Database (MCD) to construct city mobility indices. The hybrid method integrates the advantages of decision trees and fuzzy clustering into an iterative algorithm for missing data imputation. Extensive experiments conducted on the MCD and three commonly used datasets demonstrate that the hybrid method outperforms other existing effective imputation methods. With the MCD’s missing values imputed by the hybrid method, and using factor analysis and principal component analysis, this paper constructs city mobility indices for 63 cities in the MCD based on the novel concept of city mobility supply and demand. The city mobility indices constructed under a hierarchical structure of mobility supply and demand indicators represent substantial city mobility knowledge discovered from mining the MCD. The proposed hybrid method represents a significant contribution to missing data imputation research.
Sanaz Nikfalazar; Chung-Hsing Yeh; Susan Bedingfield; Hadi Akbarzadeh Khorshidi. A Hybrid Missing Data Imputation Method for Constructing City Mobility Indices. Communications in Computer and Information Science 2019, 135 -148.
AMA StyleSanaz Nikfalazar, Chung-Hsing Yeh, Susan Bedingfield, Hadi Akbarzadeh Khorshidi. A Hybrid Missing Data Imputation Method for Constructing City Mobility Indices. Communications in Computer and Information Science. 2019; ():135-148.
Chicago/Turabian StyleSanaz Nikfalazar; Chung-Hsing Yeh; Susan Bedingfield; Hadi Akbarzadeh Khorshidi. 2019. "A Hybrid Missing Data Imputation Method for Constructing City Mobility Indices." Communications in Computer and Information Science , no. : 135-148.
Chun-Chun Wei; Chung-Hsing Yeh; Ian Wang; Bernie Walsh; Yang-Cheng Lin. Deep Neural Networks for New Product Form Design. Proceedings of the 16th International Conference on Informatics in Control, Automation and Robotics 2019, 1 .
AMA StyleChun-Chun Wei, Chung-Hsing Yeh, Ian Wang, Bernie Walsh, Yang-Cheng Lin. Deep Neural Networks for New Product Form Design. Proceedings of the 16th International Conference on Informatics in Control, Automation and Robotics. 2019; ():1.
Chicago/Turabian StyleChun-Chun Wei; Chung-Hsing Yeh; Ian Wang; Bernie Walsh; Yang-Cheng Lin. 2019. "Deep Neural Networks for New Product Form Design." Proceedings of the 16th International Conference on Informatics in Control, Automation and Robotics , no. : 1.
Accounting results are crucial information closely monitored by managers, investors and government agencies for decision making. Understanding various endogenous and exogenous business factors affecting accounting results is an essential step in managing them. However, how to model the relationship between accounting results and their business factor antecedents remains an unresolved issue. To address this issue, this paper develops neural network (NN) models for modelling complex interactions between the business factors and accounting results. Based on empirical data from an international leading oil and gas company, 15 original data points, 8 inputs and 6 outputs are used, and 4 NN architectures in 2 training settings are tested. The experiments conducted show satisfactory results. Comparisons of various training settings suggest that a recurrent NN architecture with multiple outputs is best suited for accounting results modelling. The relative contribution factor analysis with the best-performing NN model provides new insights in understanding crucial business factors for the case company and accounting professionals to manage accounting results. As a pilot study, this paper contributes to business, accounting and finance research by providing a promising approach for accounting results modelling.
Yang Duan; Chung-Hsing Yeh; David L. Dowe. Accounting Results Modelling with Neural Networks: The Case of an International Oil and Gas Company. Privacy Enhancing Technologies 2018, 275 -285.
AMA StyleYang Duan, Chung-Hsing Yeh, David L. Dowe. Accounting Results Modelling with Neural Networks: The Case of an International Oil and Gas Company. Privacy Enhancing Technologies. 2018; ():275-285.
Chicago/Turabian StyleYang Duan; Chung-Hsing Yeh; David L. Dowe. 2018. "Accounting Results Modelling with Neural Networks: The Case of an International Oil and Gas Company." Privacy Enhancing Technologies , no. : 275-285.
Effective crisis management is of utmost importance for an airline to restore its safety reputation after a crash accident. Motivated by two consecutive crash accidents by the same airline, this paper proposes an importance-based method to evaluate the airline's performance as a means of identifying areas that can best improve its capabilities for effective crisis management. A four-dimensional framework with 31 attributes is identified to represent an airline's capabilities for achieving effective crisis management. Based on expert surveys, a revised importance-performance analysis method and an importance-weighted priority ranking method are used to evaluate the case airline's crisis management capabilities and identify the ways by which its future crisis management performance can be best improved. The evaluation results highlight the significant role played by the attribute importance and the need for the case airline to direct more overall improvement efforts to the organizational aspects of its crisis management practices. This paper makes conceptual and methodological contributions to crisis management research and provides useful insights into effective airline crisis management for the airline industry.
Yu-Hern Chang; Chung-Hsing Yeh; Pei-Syuan Wu. Evaluating airline crisis management performance: The cases of flights GE222 and GE235 crash accidents. Journal of Air Transport Management 2018, 70, 62 -72.
AMA StyleYu-Hern Chang, Chung-Hsing Yeh, Pei-Syuan Wu. Evaluating airline crisis management performance: The cases of flights GE222 and GE235 crash accidents. Journal of Air Transport Management. 2018; 70 ():62-72.
Chicago/Turabian StyleYu-Hern Chang; Chung-Hsing Yeh; Pei-Syuan Wu. 2018. "Evaluating airline crisis management performance: The cases of flights GE222 and GE235 crash accidents." Journal of Air Transport Management 70, no. : 62-72.
Yan Xu; Ling Zhang; Chung-Hsing Yeh; Yao Liu. Evaluating WEEE recycling innovation strategies with interacting sustainability-related criteria. Journal of Cleaner Production 2018, 190, 618 -629.
AMA StyleYan Xu, Ling Zhang, Chung-Hsing Yeh, Yao Liu. Evaluating WEEE recycling innovation strategies with interacting sustainability-related criteria. Journal of Cleaner Production. 2018; 190 ():618-629.
Chicago/Turabian StyleYan Xu; Ling Zhang; Chung-Hsing Yeh; Yao Liu. 2018. "Evaluating WEEE recycling innovation strategies with interacting sustainability-related criteria." Journal of Cleaner Production 190, no. : 618-629.
Yu-Hern Chang; Chung-Hsing Yeh. Corporate social responsibility and customer loyalty in intercity bus services. Transport Policy 2017, 59, 38 -45.
AMA StyleYu-Hern Chang, Chung-Hsing Yeh. Corporate social responsibility and customer loyalty in intercity bus services. Transport Policy. 2017; 59 ():38-45.
Chicago/Turabian StyleYu-Hern Chang; Chung-Hsing Yeh. 2017. "Corporate social responsibility and customer loyalty in intercity bus services." Transport Policy 59, no. : 38-45.
This paper proposes a new iterative fuzzy clustering (IFC) algorithm to impute missing values of datasets. The information provided by fuzzy clustering is used to update the imputed values through iterations. The performance of the IFC algorithm is examined by conducting experiments on three commonly used datasets and a case study on a city mobility database. Experimental results show that the IFC algorithm not only works well for datasets with a small number of missing values but also provides an effective imputation result for datasets where the proportion of missing data is high.
Sanaz Nikfalazar; Chung-Hsing Yeh; Susan Bedingfield; Hadi A. Khorshidi. A new iterative fuzzy clustering algorithm for multiple imputation of missing data. 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) 2017, 1 -6.
AMA StyleSanaz Nikfalazar, Chung-Hsing Yeh, Susan Bedingfield, Hadi A. Khorshidi. A new iterative fuzzy clustering algorithm for multiple imputation of missing data. 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). 2017; ():1-6.
Chicago/Turabian StyleSanaz Nikfalazar; Chung-Hsing Yeh; Susan Bedingfield; Hadi A. Khorshidi. 2017. "A new iterative fuzzy clustering algorithm for multiple imputation of missing data." 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) , no. : 1-6.
This paper develops a task assignment decision support (TADS) system for an IT service manager to assign one or multiple tasks to the most suitable IT analysts. Developed for overcoming the deficiencies of the current task assignment practice in a case company, the TADS system approaches the task assignment problem in a novel and effective manner. With a decision rule knowledge base, a multiattribute decision making model and an optimization model, the TADS system can help make rational, consistent and informed decisions under various decision settings. An empirical study is conducted on both single and multiple task assignments to demonstrate the feasibility and effectiveness of the TADS system.
Yang Duan; Chung-Hsing Yeh. TADS: A task assignment decision support system for IT services. 2016 IEEE 11th Conference on Industrial Electronics and Applications (ICIEA) 2016, 2472 -2477.
AMA StyleYang Duan, Chung-Hsing Yeh. TADS: A task assignment decision support system for IT services. 2016 IEEE 11th Conference on Industrial Electronics and Applications (ICIEA). 2016; ():2472-2477.
Chicago/Turabian StyleYang Duan; Chung-Hsing Yeh. 2016. "TADS: A task assignment decision support system for IT services." 2016 IEEE 11th Conference on Industrial Electronics and Applications (ICIEA) , no. : 2472-2477.
This paper develops a new approach to sustainable planning of WEEE recycling innovation strategies for meeting the best sustainable innovation interests of a WEEE management company. A fuzzy multi-attribute decision making algorithm is used to evaluate the to-be implemented innovation strategies in terms of their readiness levels on identified sustainability-related key risk factors (SRFs) under the environmental, economic, and social dimensions. A series of optimal weighting models are developed to determine the optimal weights for the three sustainability dimensions and their associated SRFs, with consideration of the company's subjective weighting preferences under its current operational settings. In practice, the sustainable planning approach provides WEEE management companies with a proactive mechanism for planning their innovation implementation in a sustainable manner. An empirical study on a leading WEEE management company is conducted to illustrate how the approach works.
Yan Xu; Chung-Hsing Yeh. Sustainable planning of WEEE recycling innovation strategies. 2016 IEEE 11th Conference on Industrial Electronics and Applications (ICIEA) 2016, 2501 -2506.
AMA StyleYan Xu, Chung-Hsing Yeh. Sustainable planning of WEEE recycling innovation strategies. 2016 IEEE 11th Conference on Industrial Electronics and Applications (ICIEA). 2016; ():2501-2506.
Chicago/Turabian StyleYan Xu; Chung-Hsing Yeh. 2016. "Sustainable planning of WEEE recycling innovation strategies." 2016 IEEE 11th Conference on Industrial Electronics and Applications (ICIEA) , no. : 2501-2506.
Airports need to manage corporate social responsibility (CSR) strategies for sustainable development. This paper develops a new structured approach for airports to evaluate, prioritize and categorize CSR strategies, using Taiwan’s Taoyuan International Airport Corporation (TIAC) as an example. Based on TIAC’s CSR-related activities, 18 CSR strategies grouped into 5 CSR goals (corporate governance and finance, green airport and environmental management, service quality and social relationship, employee and work environment management, and safety and security) are identified using the CSR value chain and diamond framework. The pairwise comparison method used in analytic hierarchy process and the decision-making trial and evaluation laboratory method are used respectively to evaluate the relative importance, feasibility and achievability of these 18 strategies and to analyze their causal relationships via expert questionnaire surveys. A new method is developed to plan and manage the implementation of CSR strategies by incorporating the viewpoints of both internal and external stakeholders, thus reflecting the practical effects and strategic implications of the CSR implementation. The result suggests that TIAC’s CSR strategies in relation to airport safety and security, service quality and corporate governance are most significant and have a high implementation priority. This paper contributes to the airport industry and CSR research by proposing a proactive mechanism for quantitatively evaluating, prioritizing and categorizing CSR strategies.
Yu-Hern Chang; Chung-Hsing Yeh. Managing corporate social responsibility strategies of airports: The case of Taiwan’s Taoyuan International Airport Corporation. Transportation Research Part A: Policy and Practice 2016, 92, 338 -348.
AMA StyleYu-Hern Chang, Chung-Hsing Yeh. Managing corporate social responsibility strategies of airports: The case of Taiwan’s Taoyuan International Airport Corporation. Transportation Research Part A: Policy and Practice. 2016; 92 ():338-348.
Chicago/Turabian StyleYu-Hern Chang; Chung-Hsing Yeh. 2016. "Managing corporate social responsibility strategies of airports: The case of Taiwan’s Taoyuan International Airport Corporation." Transportation Research Part A: Policy and Practice 92, no. : 338-348.
City sustainability evaluation can be formulated as a multi-criteria decision making (MCDM) problem where the interactions and weights of interdependent criteria cannot be subjectively and reliably obtained. This paper develops an objective weighting approach to determining the weights of interdependent criteria in the context of MCDM. Equipped with a novel optimization model, this approach can objectively obtain the interaction coefficients and weights of the criteria on a multi-level hierarchy. An empirical study on the sustainability performance evaluation of 13 cities in China is conducted to illustrate how the approach works. The result shows that the approach can reflect the performance divergence of the cities on each criterion and ensure that the evaluation result is not affected by the inconsistency of subjective judgments. This approach is indeed a new contribution to the methodological development of MCDM research and to the practical application of city sustainability evaluation.
Ling Zhang; Yan Xu; Chung-Hsing Yeh; Yao Liu; Dequn Zhou. City sustainability evaluation using multi-criteria decision making with objective weights of interdependent criteria. Journal of Cleaner Production 2016, 131, 491 -499.
AMA StyleLing Zhang, Yan Xu, Chung-Hsing Yeh, Yao Liu, Dequn Zhou. City sustainability evaluation using multi-criteria decision making with objective weights of interdependent criteria. Journal of Cleaner Production. 2016; 131 ():491-499.
Chicago/Turabian StyleLing Zhang; Yan Xu; Chung-Hsing Yeh; Yao Liu; Dequn Zhou. 2016. "City sustainability evaluation using multi-criteria decision making with objective weights of interdependent criteria." Journal of Cleaner Production 131, no. : 491-499.
Selecting operation alternatives for processing a recycling job is an important decision in managing e-waste recycling operations. This paper develops a novel approach to making selection decisions for e-waste recycling operations based on their sustainability performance under environmental, economic, and social dimensions. This approach addresses two new and important issues under a new selection problem structure. A job-oriented assessment method with a fuzzy knowledge base is constructed to address the first issue of how to consistently assess the performance of operation alternatives for a given recycling job with the precise or imprecise specification of the job attributes. A sustainability-based optimal weighting model is developed to address the second issue of how to determine optimal weighting for the three sustainability dimensions to reflect the company’s sustainability concerns and priorities under specific operational settings. With the assessment method and the optimal weighting model, the overall sustainability performance of each operation alternative for a given recycling job can be obtained, on which the selection decision can be made. To examine the effectiveness of the approach, an empirical study on an e-waste operation alternatives selection problem of an Australian e-recycler is conducted. The job-oriented sustainability-based selection approach significantly enhances the efficiency, consistency, and sustainability of processing e-waste recycling jobs.
Yan Xu; Chung-Hsing Yeh. Sustainability-based selection decisions for e-waste recycling operations. Annals of Operations Research 2016, 248, 531 -552.
AMA StyleYan Xu, Chung-Hsing Yeh. Sustainability-based selection decisions for e-waste recycling operations. Annals of Operations Research. 2016; 248 (1-2):531-552.
Chicago/Turabian StyleYan Xu; Chung-Hsing Yeh. 2016. "Sustainability-based selection decisions for e-waste recycling operations." Annals of Operations Research 248, no. 1-2: 531-552.