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IntroductionWorldwide supplies are being utilized at a disturbing rate and to a significant degree, the building business has been accountable for this ecological deprivation, particularly because of its elevated level of energy expenditure. Hence, this research paper targets the customers of green building industries in Taiwan and developed a framework based on Carroll’s corporate social responsibility (CSR) model, theory of planned behavior (TPB), and cognitive consistency theory (CCT), to measure the impact of CSR on green purchase intention (GPI). Furthermore, it analyzes the impact of CSR on green word of mouth (GWOM), green attitude (GA), green concern (GC), and green trust (GT). Moreover, it explores the roles of GA, GC, GWOM, and GT on GPI. Finally, to study the mediating roles of GC, GA, and GWOM, with the relationship between CSR and GPI.MethodsThe data for this study was collected from 600 customers of green building businesses located in Taiwan with the help of a convenience sampling technique.ResultsAs per the results of this research, CSR was discovered to have a positive impact on GPI, GWOM, GA, GC, and GT. Furthermore, GWOM had a significant impact on GPI. Moreover, GC and GT were in a significant relationship with GPI. Consequently, all the relationships were significant except the relationship between GA and GPI. Furthermore, GT, GWOM, and GC fully mediate the relationship between CSR and GPI. However, GA was not found to significantly mediate the relationship between CSR and GPI.DiscussionThe findings of this study provide practical implications regarding the impact of CSR on GPI and the trending issue of sustainable career development.

A methodology based on the integration of a seismic-based artificial neural network (ANN) model and a geographic information system (GIS) to assess water leakage and to prioritize pipeline replacement is developed in this work. Qualified pipeline break-event data derived from the Taiwan Water Corporation Pipeline Leakage Repair Management System were analyzed. “Pipe diameter,” “pipe material,” and “the number of magnitude-3 + earthquakes” were employed as the input factors of ANN, while “the number of monthly breaks” was used for the prediction output. This study is the first attempt to manipulate earthquake data in the break-event ANN prediction model. Spatial distribution of the pipeline break-event data was analyzed and visualized by GIS. Through this, the users can swiftly figure out the hotspots of the leakage areas. A northeastern township in Taiwan, frequently affected by earthquakes, is chosen as the case study. Compared to the traditional processes for determining the priorities of pipeline replacement, the methodology developed is more effective and efficient. Likewise, the methodology can overcome the difficulty of prioritizing pipeline replacement even in situations where the break-event records are unavailable. [ABSTRACT FROM AUTHOR]

This work focused on developing an approach for prioritizing the order of pipe replacement in a water distribution system (WDS) using a seismic-based artificial neural network (ANN). The qualified earthquake data obtained from the Taiwan Water Corporation Leakage Repair Management System (TWC-LRMS) were classified to build the model that was analyzed by both backward propagation network (BPN) and radial basis function network (RBFN). Pipe diameter, pipe material, and the number of monthly magnitude-3+ earthquakes provide the input parameters of the seismic-based ANN model for anticipating the priority of pipe replacement. The WDS of Yilan County, which frequently suffers from earthquakes in northeastern Taiwan, was used as the object of the case study. A comparison of the accuracy and reliability of the prediction model between BPN and RBFN demonstrated that RBFN outperformed BPN. The seismic-based ANN model developed in this work is streamlined for establishing a priority project of pipe replacement. The number of breaks predicted by the ANN model was close to the observed data. Furthermore, ANN has qualified as an effective technology for developing feasible pipe replacement priority in the domain of water leakage management. [ABSTRACT FROM AUTHOR]

Although regionalization policies have been proven as good strategies for municipal solid waste (MSW) management in previous studies, the optimal allocation of the waste stream is significantly affected by several influential factors, thus further investigation of the impacts of these factors on regional MSW management strategies is necessary. This study demonstrated the impacts of waste-to-electricity transformation coefficient (WETC) of incinerators and the fluctuation of unit tipping fees on the regional MSW flow/allocation of the Taipei metropolitan area from practical and economic perspectives. Real-world data and linear programming were used to obtain the least-cost alternatives under different scenarios. Analytical results indicated some treatment facilities had geographic superiority and their priorities changed when actual WETCs of incinerators were considered. Treatment facilities located at weighted centers were identified. The allocation of MSW among incinerators and landfills is affected by fluctuation of unit tipping fees within a certain range. Treatment facilities sensitive to the changes in unit tipping fees were also identified. Regression equations were also established that can estimate the cost items of MSW management scenarios with different unit tipping fees. The results of this study are very useful for daily basis regulation of MSW administration. [ABSTRACT FROM AUTHOR]

The optimization problems of water distribution networks are complex, multi-modal and discrete-variable problems that cannot be easily solved with conventional optimization algorithms. Heuristic algorithms such as genetic algorithms, simulated annealing, tabu search and ant colony optimization have been extensively employed over the last decade. This article proposed an optimization procedure based on the scatter search (SS) framework, which is also a heuristic algorithm, to obtain the least-cost designs of three well-known looped water distribution networks (two-loop, Hanoi and New York networks). The computational results obtained with the three benchmark instances indicate that SS is able to find solutions comparable to those provided by some of the most competitive algorithms published in the literature. [ABSTRACT FROM AUTHOR]

Municipal solid waste (MSW) management is a major concern for highly urbanized societies. Among proposed MSW management systems, regionalization programs generally have received considerable attention. This study analyzes real-world operational data to assess different MSW management policies, especially regionalization strategies, and their impact on MSW management systems in the Taipei metropolitan area. Linear programming is also used to identify the minimum costs sustained by each policy. The linear programming results show that regionalization programs are more economical and also improve incinerator operation efficiency. Sensitivity analysis indicates that the minimum treatment requirement of incinerators is a very sensitive influence on the MSW flows distributed through the entire region. The MSW of several "sensitive" administrative districts will be allocated to different treatment facilities according to different management strategies. A list of preferential sequences of MSW treatment and disposal facilities can also be identified by the model presented in this study. The results of this study may provide a useful tool for aiding decision-making related to real-world MSW management problems. [ABSTRACT FROM AUTHOR]

Measures the vertical air pollutant concentrations in Taiwan with the use of a tethered balloon during field campaigns in the winters of 1999 and 2001. Meteorological data; Surface concentrations; Temporal variations of the concentrations of carbon monoxide, sulfur dioxide, nitrogen oxides and ozone.