ABSTRACT
Since late 2019, the explosive outbreak of Coronavirus Disease 19 (COVID-19) has emerged as a global threat, necessitating a worldwide overhaul of public health systems. One critical strategy to prevent virus transmission and safeguard public health, involves deploying Nucleic Acid Testing (NAT) sites. Nevertheless, determining the optimal locations for public NAT sites presents a significant challenge, due to the varying number of sites required in different regions, and the substantial influences of population, the population heterogeneity, and daily dynamics, on the effectiveness of fixed location schemes. To address this issue, this study proposes a data-driven framework based on classical location-allocation models and bi-objective optimization models. The framework optimizes the number and location of NAT sites, while balancing various cost constraints and adapting to population dynamics during different periods of the day. The bi-objective optimization process utilizes the Knee point identification (KPI) algorithm, which is computationally efficient and does not require prior knowledge. A case study conducted in Shenzhen, China, demonstrates that the proposed framework provides a broader service coverage area and better accommodates residents' demands during different periods, compared to the actual layout of NAT sites in the city. The study's findings can facilitate the rapid planning of primary healthcare facilities, and promote the development of sustainable healthy cities.
ABSTRACT
Identifying factors influencing the viability of medium, small, and micro scale construction firms (MSMSCFs) is a crucial precursor in positioning such firms to aid economic and infrastructural development, especially in developing countries. This article assesses viability factors that are influenced by building information modeling (BIM) in MSMSCFs amidst construction firms' viability factors. Out of a total of 177 workers surveyed from 59 MSMSCFs that were awarded construction project contracts in sampled institutions in Nigeria, 65 staff members from 31 MSMSCFs were accessed. The factors were ranked and reduced to significant ones through principal component analysis. Ten significant factors influence the viability of MSMSCFs and six of them are enhanced by BIM implementations. All eight component factors and 18 of the 27 variables with high factor loadings can be influenced by BIM implementation. BIM can potentially curb corruption in construction projects and enhance MSMSCFs' quality of service, clients' satisfaction, construction management and technology, professional performance, procurement practices, and prompt payment of work certificates. All stakeholders need to pay prompt attention to factors that can be influenced by BIM to improve the viability of MSMSCFs, thereby hastening BIM adoption and utilization, especially in developing countries.
ABSTRACT
During last decade there is a constant increase in number of new properties built in Zagreb. There is a large number of new residences, as well as business buildings constructed, with a direct impact on revenue increase of construction companies working in Zagreb area. Regardless of the fact that number of Zagreb population has not changed significantly in last decade, there is an increase of new buildings followed by significant price increase of real estate, especially during last five years. Lack of commercial, or business buildings in Zagreb, as well as workplace deficit in Slavonia have an impact on demand growth in Zagreb real estate sector. With additional flow of Croatian students to Zagreb, demand for quality accommodation has a direct impact on real estate selling price. Recently there was a significant price increase of material and labor, which had additional impact of real estate price increase. Goal of this paper is to analyze available public data that represents material price change, as well as to analyze financial reports of biggest construction companies from Zagreb area. Analyzed data should display impact of material and labor price increase on real estate price increase, and what could be anticipated in following years.
ABSTRACT
The implementation of the urban underground logistics system (ULS) can effectively mitigate the contradiction between the surging logistics demand and the increased negativity of urban logistics. The widespread implementation of ULS still suffers from a lack of research into its operation in the marketplace, although the research on ULS system technology and network design appears to be sufficient. A new supply chain for logistics service based on ULS (ULS-SSC) was proposed, as ULS embedded in the urban logistics system could lead to the evolution of the role of supply chain participants. This article analyzed the organizational structure and operation characteristics of ULS-SSC and designed a top-down ULS-SSC operation process model based on the designed functional structure and subsystems relationship using the hierarchical colored Petri net (HCPN). The simulation results show that the integrated information management platform based on ULS can integrate urban logistics service supply chain resources and operate effectively under the two main service modes designed. The high-time delay intermediate links can be upgraded by system optimization, and the links with initial pickup and terminal distribution can be improved through outsourcing and supply chain collaboration. The findings provide new insights into the feasibility of the operation of ULS in the market and help stimulate the implementation of ULS.
ABSTRACT
An unreasonable design hourly volume (DHV) greatly impacts road facility construction costs and traffic efficiency. With the rapid rise in the tourism economy and widespread emergence of holiday travel characteristics in China, DHV applicability for suburban expressways requires verification. This study collected annual traffic volume data over 8760 h along Xi’an Ring Expressway from 2017 to 2019. Traffic demand distribution patterns throughout the year and peak hours were analyzed on the basis of the descending order of the obtained hourly traffic volume (HV) and factor data. HV distribution characteristics, 30th highest hourly volume (30 HV) typicality, and DHV factor applicability were investigated. Due to travel characteristics under the background of the tourism economy, the peak HV distribution exhibits polarization characteristics. The recommended value of the design hour traffic factor in the specification corresponded to a number of hours greater than 200, with the 30 HV factor under the background of the tourism economy being 25% higher than the recommended value. Considering the tourism economy, the high level of traffic operation time increased significantly, and the characteristics of a sharp decline in the peak HV disappeared. The 30 HV factor no longer exhibited traditional characteristics. The design causes of traffic congestion are identified herein.
ABSTRACT
During the COVID-19 epidemic, the Chinese central government adopted a dynamic clearing prevention and control strategy. Meanwhile, most local governments issued policies to incorporate normal epidemic prevention costs into the costs of construction projects. However, there are few provisions on how to determine the calculation standards for these costs. To accurately predict the normalized epidemic prevention costs of construction projects from different aspects, the relevant factors that affect epidemic prevention costs are investigated and an optimized neural network prediction method that can effectively eliminate abnormal data with a too large deviation is proposed. The results show that compared with the traditional backpropagation (BP) neural network and BP neural networks optimized by genetic algorithm, the error of the optimized neural network achieves a smaller error in predicting the normalized epidemic prevention costs of construction projects (the average error of the traditional BP neural networks is 6%). Meanwhile, among the factors that affect epidemic prevention costs, total investment, project category, and construction scale have the greatest impact. Based on the research results, this paper proposes pricing suggestions and corresponding management solutions for the epidemic prevention costs of construction projects, which will be helpful to project managers. [ FROM AUTHOR] Copyright of Mathematical Problems in Engineering is the property of Hindawi Limited and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
ABSTRACT
Trombe walls figure among many passive devices used in the Mediterranean climate to minimize heating demands in residential buildings. The thickness of this massive wall is a critical parameter that influences the effectiveness of the system. Insufficient wall thickness conducts to an important interior temperature fluctuation, and huge wall thickness will increase costs and thermal resistance. In this paper, the optimum thickness of four different construction materials (concrete, stone, adobe, and brick), which can be used in the Trombe wall, was determined using an energetic and economic analysis. The energetic results with TRNSYS software show that the best materials, which can contribute to a reduction by 50% in heating loads of a single room, are stone and concrete. For the economic analysis, the life cycle cost and the payback period were calculated for each construction material. The results show that the optimum thickness for stone and concrete are, respectively, 34 and 32 cm with a payback period of 2.85 and 2.65 years.
ABSTRACT
During the COVID-19 pandemic, construction accidents in the United States (US) dropped dramatically compared to previous years. This research uses Saunders’ research onion approach to conduct a deep and systematic analysis of pre- and post-COVID-19 data to understand this phenomenon. The proposed research framework examines safety and prevention measures implemented by the US government, using data collected from various US government agencies, including the Occupational Safety and Health Administration (OSHA), Centers for Disease Control and Prevention (CDC), and US Bureau of Labor Statistics. COVID-19’s effects on construction site health and safety were analyzed and ranked in order of efficacy in a hierarchy of control, and findings reveal a number of safety measures that can potentially be implemented to promote improved construction safety even after COVID-19 is over.
ABSTRACT
Shipping emissions, especially those in port areas, have become one of the main concerns of the maritime industry. Shore power has been recognized as a promising way to alleviate the problem. However, shore power has not been extensively adopted in China. Therefore, from the government’s point of view, this paper conducts a case study of the shore power deployment problem based on the real container shipping network of China, including the Port of Hong Kong. In addition to the basic case, we, also, conduct numerical experiments with different budgets, to analyze its influence on the optimal subsidy plan and cost–benefit analysis. The results give two useful managerial insights: (i) it might be unnecessary to spend a large amount of the budget on subsidization, and (ii) the subsidy expenditure needs to be considered together with the final bunker reduction, while creating the budget.
ABSTRACT
This paper examines the current use of panelized components in homebuilding in the Oklahoma City (OKC) and Dallas-Fort Worth (DFW) areas. Panelization is a type of prefabrication in which certain framing components are built off site and then transported to the site for assembly. This technique has been reported to make homebuilding more efficient and affordable. Further, panelization may be one strategy to cope with the growing labor shortage. However, adoption in the United States varies and is relatively limited. To better understand the benefits and challenges of panelization, semi-structured interviews were conducted with 10 production homebuilders from the OKC and DFW metropolitan areas. Although most of the benefits (faster, more consistent, and less waste) and challenges (cost, logistics, and labor issues) were consistent with previous research, new benefits related to warranties and new challenges relating to transportation and delivery were identified. In addition, the study concludes that national and regional production builders differ in their priorities and perceptions of panelization: national builders are trying to increase their use of panelization, whereas regional builders are moving away from it.
ABSTRACT
With the rapid expansion of prefabricated construction in China, significant changes in safety performance are still unapparent for numerous prefabricated constructions, and safety accidents are constantly exposed in public. The ignorance of interactions among safety risks impedes efficacious improvement, which instructs the need for a thorough analysis of these interactions based on complex network theory. This paper starts with the identification of 37 safety risks refined through literature review and expert interviews, and 90 interrelationships among them verified by virtue of the questionnaire survey, laying a foundation for the establishment of a prefabricated construction safety risk network (PCSRN). The topological analysis results prove that PCSRN is a scale-free as well as a small-world network, which indicates the high-efficiency propagation and diffusion among safety risks in prefabricated constructions. Moreover, eight critical nodes are identified with four different ranking criteria, and corresponding safety strategies are proposed to address them. The developed method not only provides a novel insight to interpret the safety risks of prefabricated construction but also has the potential to advance safety performance of this sector.
ABSTRACT
Multi-center location of pharmaceutical logistics is the focus of pharmaceutical logistics research, and the dynamic uncertainty of pharmaceutical logistics multi-center location is a difficult point of research. In order to reduce the risk and cost of multi-enterprise, multi-category, large-volume, high-efficiency, and nationwide centralized medicine distribution, this study explores the best solution for planning medicine delivery for the medicine logistics. In this paper, based on the idea of big data, comprehensive consideration is given to uncertainties in center location, medicine type, medicine chemical characteristics, cost of medicine quality control (refrigeration and monitoring costs), delivery timeliness, and other factors. On this basis, a multi-center location- and route-optimization model for a medicine logistics company under dynamic uncertainty is constructed. The accuracy of the algorithm is improved by hybridizing the fuzzy C-means algorithm, sequential quadratic programming algorithm, and variable neighborhood search algorithm to combine the advantages of each. Finally, the model and the algorithm are verified through multi-enterprise, multi-category, high-volume, high-efficiency, and nationwide centralized medicine distribution cases, and various combinations of the three algorithms and several rival algorithms are compared and analyzed. Compared with rival algorithms, this hybrid algorithm has higher accuracy in solving multi-center location path optimization problem under the dynamic uncertainty in pharmaceutical logistics.
ABSTRACT
The building sector continues to play an essential role in reducing worldwide energy consumption. The reduced consumption is accompanied by stricter regulation for the thermotechnical design of the building envelope. The redefined nearly Zero Energy Building levels that will come into force for each member state will pressure designers to rethink the constructive details so that mandatory levels can be reached, without increasing the construction costs over an optimum level but at the same time reducing greenhouse gas emissions. The paper aims to illustrate the main conclusions obtained in assessing the thermo-energy performance of a steel-framed building representing a holistically designed modular laboratory located in a moderate continental temperate climate, characteristic of the south-eastern part of the Pannonian Depression with some sub-Mediterranean influences. An extensive numerical simulation of the main junctions was performed. The thermal performance was established in terms of the main parameters, the adjusted thermal resistances and global thermal insulation coefficient. Further on, the energy consumption for heating was established, and the associated energy rating was in compliance with the Romanian regulations. A parametric study was done to illustrate the energy performance of the investigated case in the five representative climatic zones from Romania. An important conclusion of the research indicates that an emphasis must be placed on the thermotechnical design of Light Steel Framed solutions against increased thermal bridge areas caused by the steel’s high thermal conductivity for all building components to reach nZEB levels. Nevertheless, the results indicate an exemplary behaviour compared to classical solutions, but at the same time, the need for an iterative redesign so that all thermo-energy performance indicators are achieved.
ABSTRACT
Purpose>This paper aims to assess COVID-19 (C-19) pandemic influence in the 37 factors identified from extant literature as factors influencing the viability of local construction firms (LCFs).Design/methodology/approach>A sample size of 65 staff of 31 LCFs that were awarded construction projects contracts in institutions in Nigeria was purposefully selected and accessed based on relevant predetermined criteria. Respondents’ views on factors determining the viability of LCFs were obtained. Factors known to be influenced by C-19 are 25 of the 37 factors rated on a five-point Likert scale of importance by the respondents. Mean scores were used to rank the factors and principal component analysis was used to obtain key component factors (CFs) influenced by the C-19 pandemic.Findings>Six of the first ten “extremely important” and “very important” factors are known to be influenced by C-19 pandemic. A total of 8 CFs having 20 variables with factor loadings of more than 0.5 each were known to be influenced by C-19. The C-19 pandemic influenced LCFs’ cash flow and management of construction labour, plant and equipment amidst variables that had above 0.8 factor loading.Research limitations/implications>A limitation of this study is the inability to conduct close contact interview during this period to obtain personal views on the influence of C-19 on LCFs. However, this does not reduce the quality of findings of this study, as there are valid literature basis hinging this study findings.Practical implications>The paper recommends that all stakeholders pay prompt attention to the factors adversely affected by the C-19 pandemic to improve or at the least sustain the viability of LCFs.Originality/value>This paper fulfils a present pertinent need of assessing the influence of the C-19 pandemic on various factors influencing the viability of construction firms.
ABSTRACT
In 2020, the sudden global epidemic of novel coronavirus pneumonia (COVID-19) caused abnormal fluctuations in the global grain market and posed severe challenges to world grain security. Therefore, it is very important for countries around the world to analyze the determinants of grain price and put forward corresponding strategies to ensure grain safety. In this paper, we theoretically discussed the relationship between financial liquidity, speculation, and grain price for the first time. Based on the analysis of Fisher's equation, this paper argues that the theoretical basis of grain financialization is closer to the volatility theory of the money market. Then, we employ the structural vector autoregression model (SVAR) to explore the impulse response of grain price to the structural shock of world grain production, demand, financial liquidity, and speculation. Our empirical results show that the effects of financial liquidity and speculation on the grain price are more significant. Meanwhile, grain demand changes caused by the global economy have no significant impact on grain price. [ FROM AUTHOR] Copyright of Scientific Programming is the property of Hindawi Limited and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)