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The purpose of this paper is to explore Taiwan’s regional energy efficiency trend and complement the work of the total-factor energy efficiency (TFEE) index proposed by Hu and Wang (2006). It further extends panel data stochastic frontier analysis (SFA) modeling for estimating disaggregate energy efficiency.

This paper applies the panel data stochastic production frontier to estimate the TFEE scores for 20 administrative regions in Taiwan over the period 2004-2015. The SFA models include five inputs (employed population, amount of productive electricity power consumed, amount of electricity consumed for household and non-household electric lighting, amount of gasoline sales, and amount of diesel sales) and one output (total real income in the base year of 2011).

This research concludes with three main findings: the inefficient administrative regions of Taiwan include mostly large industrial parks and the petrochemical industry cluster; the top five administrative regions with inefficient diesel use are mostly metropolitan areas that the concern of air pollution caused by diesel system arouses the awareness to use less diesel fuel; and the average TFEE score on household and non-household electric lighting is higher than the usage efficiency of productive electricity power, gasoline, and diesel, but there is still room for efficiency improvement.

Most administrative regions in Taiwan are not efficient in almost all kinds of energy use. The results show that the efficiencies of using productive electricity power, gasoline, and diesel need to be improved a lot more.

As a strand in industrialization movement in architecture, engineering and construction (AEC) industry, prefabricated construction (PC) has gained widespread popularity due to high efficiency, energy saving, low environmental impacts, safety and other advantages of PC. Well-managed supply chain can further leverage the advantages of PC. However, there is a lack of more systematically overview of the prefabricated construction supply chain (PCSC). This paper aims to comb the current status and look into the future direction of PCSC by reviewing the existing research.

In total, 131 articles related to prefabricated construction supply chain management (PCSCM) from 2000 to 2022 have been collated to (1) conduct a bibliometric analysis by using VOSviewer, including the literature sources, keywords co-occurrence, co-authorships, authorship citation and country active in the field of PCSCM; (2) classify and summarize the status of research in PCSCM through qualitative discussion and (3) point out the future research directions.

In total, 131 articles are carried out for bibliometric analysis and in-depth qualitative discussion, the visualization maps and the main research themes in the field of PCSCM are obtained. The results show that supply chain intelligentization and informatization are hot topics. Finally, future research directions that should be paid attention to in the field of PCSCM are pointed out.

This study can help project managers understand the current status and problems of PCSC operations and provide a basis for future management decisions.

Compared with previous studies, this study adds the dimension of “article authorship” to the quantitative analysis and discusses the research themes in the field of PCSCM in a comprehensive manner. In addition, this paper deeply discusses the main research topics from both the specific contents and research methods adopted.

By introducing the mass customization service mode into the cloud logistics environment, this paper studies the joint optimization of service provider selection and customer order decoupling point (CODP) positioning based on the mass customization service mode to provide customers with more diversified and personalized service content with lower total logistics service cost.

This paper addresses the general process of service composition optimization based on the mass customization mode in a cloud logistics service environment and constructs a joint decision model for service provider selection and CODP positioning. In the model, the two objective functions of minimum service cost and most satisfactory delivery time are considered, and the Pareto optimal solution of the model is obtained via the NSGA-II algorithm. Then, a numerical case is used to verify the superiority of the service composition scheme based on the mass customization mode over the general scheme and to verify the significant impact of the scale effect coefficient on the optimal CODP location.

(1) Under the cloud logistics mode, the implementation of the logistics service mode based on mass customization can not only reduce the total cost of logistics services by means of the scale effect of massive orders on the cloud platform but also make more efficient use of a large number of logistics service providers gathered on the cloud platform to provide customers with more customized and diversified service content. (2) The scale effect coefficient directly affects the total cost of logistics services and significantly affects the location of the CODP. Therefore, before implementing the mass customization logistics service mode, the most reasonable clustering of orders on the cloud logistics platform is very important for the follow-up service combination.

The originality of this paper includes two aspects. One is to introduce the mass customization mode in the cloud logistics service environment for the first time and summarize the operation process of implementing the mass customization mode in the cloud logistics environment. Second, in order to solve the joint decision optimization model of provider selection and CODP positioning, this paper designs a method for solving a mixed-integer nonlinear programming model using a multi-layer coding genetic algorithm.

The purpose of this paper is to investigate the mechanical properties’ behaviors of woven composite cut-out structures with specific parameters. Because of the complexity of micro-scale and meso-scale structure, it is difficult to accurately predict the mechanical material behavior of woven composites. Numerical simulations are increasingly necessary for the design and optimization of test procedures for composite structures made by the woven composite. The results of the proposed method are well satisfied with the results obtained from the experiment and other studies. Moreover, parametric studies on different plates based on the stacking sequences are investigated.

A multi-scale modeling approach is suggested. Back-propagation neural networks (BPNN), radial basis function (RBF) and least square support vector regression are integrated with efficient global optimization (EGO) to reduce the weight of assigned structure. Optimization results are verified by finite element analysis.

Compared with other similar studies, the advantage of the suggested strategy uses homogenized properties behaviors with more complex analysis of woven composite structures. According to investigation results, it can be found that 450/−450 ply-orientation is the best buckling load value for all the cut-out shape requirements. According to the optimal results, the BPNN-EGO is the best candidate for the EGO to optimize the woven composite structures.

A multi-scale approach is used to investigate the mechanical properties of a complex woven composite material architecture. Buckling of different cut-out shapes with the same area is surveyed. According to investigation, 45°/−45° ply-orientation is the best for all cut-out shapes. Different surrogate models are integrated in EGO for optimization. The BPNN surrogate model is the best choice for EGO to optimization difficult problems of woven composite materials.

The purpose of this paper is to study the effects of single parameters for temperature characteristics of oil film in port plate pair and the relationship of calculated results and experimental results under different viscosity.

The paper established the mathematical model of oil film of port plate pair, calculated the energy equation of port plate pair, simulated for the oil film and temperature distribution and selected different kinds of lubricants to analyze the calculated value and the experimental value.

The results show: temperature rise of port plate pair is reduced with the increase of oil viscosity; temperature rise of port plate pair is decreased with rise of initial oil film thickness; temperature rise of port plate pair is increased with the rise of cylinder body speed, inclination angle and sealing belt width; and through the comparison of calculated value and experimental value, under the same viscosity and cylinder speed, experimental results are bigger.

This paper used the methods that the temperature of port plate pair was calculated numerically, and the results were consistent with experimental results, so it can get high precision.

The purpose of this paper is to explore recent national human resource development (NHRD) practices in China through a literature review focusing on programs and activities that represent the roles and interactions among the government, industry and universities.

To effectively consolidate previous work and conceptualize the recent development of the NHRD practices in China, a semi-narrative literature review was used to explore and analyze NHRD-related functions and activities.

Findings from the literature review showed that although the central government still plays a predominant role in China, universities and corporations are increasingly playing a critical role in developing an innovative and skilled workforce. At the regional level, NHRD initiatives in China have been increasingly undertaken by universities, industry and government–industry–university collaborations. The authors also found a disparity between developed and underdeveloped regions in terms of NHRD in China.

This study used the triple helix model as a framework that provides an insightful lens for researchers to examine how various social entities interact with each other and jointly contribute to NHRD. Further case studies are needed to generate evidence-based knowledge to the NHRD literature.

A more systematic NHRD leadership structure at both the national and local level is desired to unleash the potential of bottom-up development and active government–industry–university collaboration. To counter regional divergence in NHRD in China, intra- and cross-regional collaborations are helpful in improving resources distribution and workforce development.

Based on open system theory, this study focused on programs and activities that represent the roles and interactions among the government, industry and university in Chinese NHRD through the lens of the triple helix model. In addition, this study offers a conceptual model of Chinese NHRD to help scholars and practitioners understand the transitional efforts in NHRD.

This study aims to examine if the participation of live-stream influencers (LSIs) affects tipping frequency on live streaming platforms, and further investigate the mediating and moderating mechanisms.

Quasi-experiment and difference-in-differences models are used for data analysis. Propensity score matching is used to address potential unobservable endogeneity.

Real-time live streaming data reveal that LSIs’ participation significantly improves tipping frequency in live streaming rooms. Also, more users are attracted to the live streaming rooms and more users become active in participation. Additionally, the positive impact of LSIs’ participation is enhanced in the live streaming rooms with a greater number of relationship links between users.

The findings clarify the new role of influencers and reveal the mechanisms on how LSIs benefit the platforms.

The findings offer novel insights into implementing influencer marketing to interactive social media platforms, by encouraging influencer participation, user relationship building and influencer network growth.

This study highlights the value of LSIs for interactive social media platforms in terms of organic growth, revenue generation and cost reduction.

Production and transportation of precast components, as two continuous service stages of a precast plant, play an important role in meeting customer needs and controlling costs. However, there is still a lack of production and transportation scheduling methods that comprehensively consider delivery timeliness and transportation economy. This article aims to study the integrated scheduling optimization problem of in-plant flowshop production and off-plant transportation under the consideration of practical constraints of customer order delivery time window, and seek an optimal scheduling method that balances delivery timeliness and transportation economy.

In this study, an integrated scheduling optimization model of flowshop production and transportation for precast components with delivery time windows is established, which describes the relationship between production and transportation and handles transportation constraints under the premise of balancing delivery timeliness and transportation economy. Then a genetic algorithm is designed to solve this model. It realizes the integrated scheduling of production and transportation through double-layer chromosome coding. A program is designed to realize the solution process. Finally, the validity of the model is proved by the calculation of actual enterprise data.

The optimized scheduling scheme can not only meet the on-time delivery, but also improve the truck loading rate and reduce the total cost, composed of early cost in plant, delivery penalty cost and transportation cost. In the model validation, the optimal scheduling scheme uses one less truck than the traditional EDD scheme (saving 20% of the transportation cost), and the total cost can be saved by 17.22%.

This study clarifies the relationship between the production and transportation of precast components and establishes the integrated scheduling optimization model and its solution algorithm. Different from previous studies, the proposed optimization model can balance the timeliness and economy of production and transportation for precast components.

The purpose of this paper is to examine a proposed model of location-based advertising (LBA) effectiveness upon the influence of integrative perceived values on consumers' attitude and behavioral responses in the immaturity of LBA in Vietnam.

A survey research method was utilized to collect data from mobile users. A real sample of 459 respondents was deemed and the Structural Equation Modeling (SEM) was applied to analyze data.

The results unveil that contextual offers, social facilitation, and advertising values have significantly positive effects on attitude; in turn, attitude mediates between these factors and purchase intention, information seeking and recommendation behaviors. Moreover, social facilitation is a significant stimulator of purchase intention. Otherwise, perceived encroached risk negatively impacts attitude.

Marketers should capture considerable attention to mobile natives' conscious awareness about a mechanism of tailoring their enthusiasm and behavioral responses at the embryonic stage of LBA growth in emerging countries like Vietnam.

This study fills the gap in the current literature by simultaneously exploring the importance of integrative perceived values to construct a hypothetical framework of consumers' responses and performance based on the uses and gratifications theory, inclusive perceived behavioral control derived from theory of planned behavior, associated with contextual value from the nature of LBA.

This study aims to suggest and develops a global sensitivity analysis-assisted multi-level sequential optimization method for the heat transfer problem.

Compared with other surrogate-assisted optimization methods, the distinctive characteristic of the suggested method is to decompose the original problem into several layers according to the global sensitivity index. The optimization starts with the several most important design variables by the support vector regression-based efficient global optimization method. Then, when the optimization process progresses, the filtered design variables should be involved in optimization one by one or the setting value. Therefore, in each layer, the design space should be reduced according to the previous optimization result. To improve the accuracy of the global sensitivity index, a novel global sensitivity analysis method based on the variance-based method incorporating a random sampling high-dimensional model representation is introduced.

The advantage of this method lies in its capability to solve complicated problems with a limited number of sample points. Moreover, to enhance the reliability of optimum, the support vector regression-based global efficient optimization is used to optimize in each layer.

The developed optimization tool is built by MATLAB and can be integrated by commercial software, such as ABAQUS and COMSOL. Lastly, this tool is integrated with COMSOL and applied to the plant-fin heat sink design. Compared with the initial temperature, the temperature after design is over 49°. Moreover, the relationships among all design variables are also disclosed clearly.

The D-MORPH-HDMR is integrated to obtain the coupling relativities among the design variables efficiently. The suggested method can be decomposed into multiplier layers according to the GSI. The SVR-EGO is used to optimize the sub-problem because of its robustness of modeling.