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Many engineering projects fail to meet their planned completion dates in real practice. This is a recurrent topic in the project management literature, with poor planning and controlling practices frequently cited among the most significant causes of delays. Unfortunately, hardly any attention has been paid to the fact that the classical scheduling techniques--Gantt chart, Critical Path Method (CPM), and Program Evaluation and Review Technique (PERT)--may not be as fit for purpose as they seem. Arguably, because of their relative simplicity, these techniques are still almost the only ones taught nowadays in most introductory courses to scheduling in many engineering and management degrees. However, by utterly ignoring or inappropriately dealing with activity duration variability, these techniques provide optimistic completion dates, while suffering from other shortcomings. Through a series of simple case studies that can be developed with a few participants and common dice, a systematic critique of the classical scheduling techniques is offered. Discussion of the case studies results illustrate why limiting the contents of scheduling education and teaching can be detrimental, as the aforementioned classical scheduling techniques cannot not provide project managers with sufficient resources to effectively plan and control real projects.

IntroductionElevated pulse pressure (ePP) is an independent marker of cardiovascular risk (CVR) in people older than 60, and a functional marker of subclinical target organ damage (sTOD) which can predict cardiovascular events in patients with hypertension (HTN), regardless of sTOD.ObjectiveTo evaluate the prevalence of ePP in adult population seen in primary care and its association with other vascular risk factors, sTOD and with cardiovascular disease (CVD).Materials and methodsObservational multicentre study conducted in Spain (8,066 patients, 54.5% women) from the prospective cohort study IBERICAN recruited in Primary Care. Pulse pressure (PP) was defined as the difference between the systolic blood pressure (SBP) and the diastolic blood pressure (DBP) ≥60 mmHg. Adjusted (for age and sex) ePP prevalence were determined. Bivariate and multivariate analyses of the possible variables associated with ePP were carried out.ResultsThe mean of PP was 52.35 mmHg, and was significantly higher (p

The adoption of digital technologies is key to the digital transformation of the construction industry. However, the current adoption of digital technologies is limited. This study uses China as a case, combines the DOI and TOE theories to identify impact factors of the adoption of digital technologies in major projects. The configuration analysis is complemented with fuzzy-set qualitative comparative analysis. As a result, the study constructs the “TOE-D Technology Adoption Antecedent Framework”, including 11 antecedents, and identifies three distinct configurations types, namely: “Needs-Resource-Collaboration”; “Resource” under high competitive pressure; and “Resource” under low competitive pressure. Comparing the configurations horizontally, the core or edge characteristics of factor in configurations are analyzed. The results can help major projects in the construction industry to ascertain a combination of elements, which promote the adoption of digital technologies so that project practitioners can make targeted and precise adjustments to enable digital transformation of the construction industry.

Science and Technology Innovation Communities (STICs) are student-led partnerships that bring together businesses, research centres, and university staff. They constitute an effective way of promoting student innovation ability. However, the students' position within the STICs organisation network may condition how their innovation ability is effectively acquired. Using Social Network Analysis (SNA), this study measures how the STICs organisation network promotes the innovation ability of its actors. The paper finds that network centrality and structural holes of the STICs organisation network are positively correlated with student innovation ability. The results are validated through robustness tests in three different STICs, involving engineering students from China's Chang'an University. Semi-structured interviews are also conducted with 20 relevant actors of STICs. The conclusion suggests that a higher involvement of core actors, more support from schools, and more restrictive entry requirements are necessary to improve the organisation management and training level of engineering students in STICs.

Abstract In China and other countries, many highway projects are built in extensive and high-altitude flat areas called plateaus. However, research on how the materialisation of these projects produce a series of ecological risks in the landscape is very limited. In this research, a landscape ecological risk analysis model for high-altitude plateaus is proposed. This model is based on the pattern of land uses of the surrounding area. Our study includes buffer analysis, spatial analysis, and geostatistical analysis. We apply the model to the Qumei to Gangba highway, a highway section located in the southeast city of Shigatse at the Chinese Tibet autonomous region. Through global and local spatial autocorrelation analysis, the spatial clustering distribution of ecological risks is also explored. Overall, our study reveals the spatial heterogeneity of ecological risks and how to better mitigate them. According to a comparison of the risk changes in two stages (before and after the highway construction), the impact of highway construction on the ecological environment can be comprehensively quantified. This research will be of interest to construction practitioners seeking to minimize the impact of highway construction projects on the ecological environment. It will also inform future empirical studies in the area of environmental engineering with potential affection to the landscape in high-altitude plateaus.

Completing a project on time and on budget are essential factors for the success of any project. One technique that allows predicting the final cost of a project is earned value management (EVM). In this technique, different mathematical methods for predicting the final project cost have been proposed over the last 30 years. These formulas make use of activities’ actual costs and durations as the project progresses. EVM is a technique widely used by many project management professionals. However, very few studies have compared the stability and accuracy of the multiple existing methods for predicting the final cost of the project (commonly abbreviated as estimated cost at completion, EAC). This study compares the stability and accuracy of 30 deterministic cost prediction methods (EAC) in EVM. For this purpose, a representative database of 4100 simulated projects of various topological structures is used. Our results suggest that the methods with the simplest mathematical configurations achieve better stability and accuracy performance. Knowing which EVM methods are the most stable and accurate for predicting the final cost of the project will help project practitioners choose the most reliable cost prediction techniques when they are managing their own projects in real contexts.

To increase the speed and efficiency of expressways construction, information management is being gradually introduced into the construction process. However, progress is limited due to the complexity of expressway engineering and application limitations of information technology. Design and delivery are still dominated by paper files, and the management of test and inspection data is still relatively extensive. Research to date into digital expressway construction has been piecemeal and fragmented with a lack of research related to the whole construction process and a data-centric information management system yet to be realized. In response, through literature research and semi-structured interviews, the framework of a data-driven digital whole-process highway construction management platform was determined. A whole process management platform was established according to the framework, and the functional application of the proposed platform was explained through a case. The framework is proposed from the perspective of the whole process of collaborative sharing., which provides a new way of thinking to solve the problems existing in the current field of expressway construction whole-process management. It also provides data-centric management, electronic design and delivery, a refined workflow, and an efficient management process.

Deciduous trees are well known for controlling solar gains in buildings, contributing to energy savings in a sector that consumes 35% of global energy. However, there is still a lack of information about the real thermal impact that deciduous trees have. This work proposes a new method that is cheap and easy to implement to quantify the shading efficiency of different types of deciduous trees in hot seasons. The results can be applied in energy evaluations of buildings. The trees selected belong to the central valley of Chile, which is characterized by hot summers and cold winters. The trees selected can also be found in other parts of the world. A spectrometer is used for measuring the amount of solar radiation (irradiance) that is present in the shadow of trees, measuring wavelengths between 339 nm and 750 nm (mostly within the visible light range). The full referential irradiance spectrum of the site is obtained by calibrating the standard ASTM G-173-03. At the site, the spectrometer is used to obtain the visible light range, while the infrared radiation (IR) and ultraviolet (UV) radiation ranges are obtained from the literature. Our results indicate that the analyzed deciduous trees reduce an average of 82% of the solar radiation. This information will help project designers during the building energy efficiency design phase by representative modeling of the solar radiation gains allowed by deciduous trees.

Since the beginning of the second industrial revolution, the use of tanks for the storage of petroleum products ensured the permanent supply of equipment that depended on fossil fuel derived from petroleum, either for direct consumption or as an element for power generation. For correct operation, periodic cleaning of these confined spaces was required, being a common practice for the direct exposure of operators to explosive atmospheres. Currently, there are many industries that keep this kind of deposit, and cleaning works are considered of high occupational risk. In this context, the question arises as to whether human–machine collaboration thanks to the technologies that compose Industry 5.0 can mitigate these risks while generating a sustainable balance by optimizing costs and protecting the environment. In the present work, the analytic hierarchy process (AHP) method is used to prioritize the requirements that should be compiled to establish safe protocols in tank cleaning works, solving the multi-criteria problem. Results prove that a couple of alternatives improve the working conditions of the people involved in this process: the chemical cleaning and the robotic cleaning, which approximately accounts for two thirds of the decision. These requirements are aligned with the Industry 5.0 paradigm, encouraging the use of robots for high-risk processes, and influencing human behavior. In addition, cost reduction is achieved without compromising on quality of service or delivery schedule, thus enabling a circular economy that promotes occupational safety in company policies.

Resource misallocation (RM) refers to the existence of marginal output inequalities between different industries or companies in an economy. Prior studies of RM have mostly focused on effect analysis, construction industry structure upgrades, and organization management. However, these studies have been fragmented and unrelated. This paper analyzes the status quo, consequences, and emerging trends of RM research at the macroscopic level based on current problems and with the aim of exploring potential solutions. Drawing on grounded theory, a qualitative analysis using text-mining is used to analyze the characteristics of 124 RM-related papers. The results more comprehensively and systematically reveal that current RM research encompasses four major dimensions of sources and concepts, misallocation degree measurement and characterization, focused issues (field), and RM research deficiencies. Methods for measuring RM have also been developed from the simple proportional method to current mainstream methods (e.g., growth rate decomposition and variant substitution). We conclude that, in order for this discipline to thrive and effectively reduce RM, future research into RM should focus on core categories, especially the reform of market-oriented factors, transformation of government functions, construction industrial structure adjustment, and methods of income distribution. This systematic review provides a discipline oversight and uncovers necessary and potential research directions.

Environmental regulations (ER) can support or dissuade the reduction of carbon emissions. However, there are limited studies on the impact of ER on carbon emissions for the transportation infrastructure. Using provincial panel data from China for the period 2001–2017, this study measures how ER can affect the carbon emissions efficiency (CEE) of transportation infrastructure. The study uses Hansen’s panel threshold model to analyze current thresholds of ER on CEE. The results show that (1) China’s transportation infrastructure during 2001–2017 experienced a 10.15% decrease of CEE; (2) there are significant heterogeneities across the regions of China regarding CEE; (3) ER produces some CEE threshold effects in China’s current transportation infrastructure. This study proposes alternative evaluation methods and theoretical frameworks for dynamically measuring the CEE of transportation infrastructure, and provides governments with improved criteria to design effective environmental policies.

In the COVID-19 era, a direct relationship has been consolidated between the concentration of the pollutant carbon dioxide (CO2) and indoor disease transmission. For reducing its spread, recommendations have been established among which air renewal is a key element to improve indoor air quality (IAQ). In this study, a low-cost CO2 measurement device was designed, developed, assembled, prototyped, and openly programmed so that the IAQ can be monitored remotely. In addition, this clonic device was calibrated for correct data acquisition. In parallel, computational fluid dynamics (CFD) modeling analysis was used to study the indoor air flows to eliminate non-representative singular measurement points, providing possible locations. The results in four scenarios (cross ventilation, outdoor ventilation, indoor ventilation, and no ventilation) showed that the measurements provided by the clonic device are comparable to those obtained by laboratory instruments, with an average error of less than 3%. These data collected wirelessly for interpretation were evaluated on an Internet of Things (IoT) platform in real time or deferred. As a result, remaining lifespan of buildings can be exploited interconnecting IAQ devices with other systems (as HVAC systems) in an IoT environment. This can transform them into smart buildings, adding value to their refurbishment and modernization.

Many engineering projects fail to meet their planned completion dates in real practice. This a recurrent topic in the project management literature, with poor planning and controlling practices frequently cited among the most significant causes of delays. Unfortunately, hardly any attention has been paid to the fact that the classical scheduling techniques: Gantt chart, Critical Path Method (CPM), and Program Evaluation and Review Technique (PERT), may not be as fit for purpose as they seem. Arguably, because of their relative simplicity, these techniques are still almost the only ones taught nowadays in most introductory courses to scheduling in many engineering and management degrees. However, by utterly ignoring or inappropriately dealing with activity duration variability, these techniques provide optimistic completion dates, while suffering from other shortcomings. Through a series of simple case studies that can be developed with a few participants and common dice, a systematic critique of the classical scheduling techniques is offered. Discussion of the case studies results illustrate why limiting the contents of scheduling education and teaching can be detrimental, as the aforementioned classical scheduling techniques cannot not provide project managers with sufficient resources to effectively plan and control real projects.

With the rapid development of new technologies, such as big data, the Internet of Things (IoT) and intelligent sensing, the traditional asphalt pavement construction quality evaluation method has been unable to meet the needs of road digital construction. At the same time, the development of such technologies enables a new management system for asphalt pavement construction. In this study, firstly, the dynamic quality monitoring system of asphalt concrete pavement is established by adopting the BeiDou Navigation Satellite System, intelligent sensing, the IoT and 5G technology. This allows key technical indicators to be collected and transmitted for the whole process of asphalt mixture, which includes the mixing plant, transport vehicle, paving and compaction. Secondly, combined with AHP and the entropy weight (EW) method, the index combination weight is calculated. The comprehensive index for the pavement digital construction quality index (PCQ) is proposed to reflect the impact of monitoring indicators on pavement quality. An expert decision-making model is formed by using the improved particle swarm optimization (PSO) algorithm coupled with radial basis function neural network (RBF). Finally, the digital monitoring index and pavement performance index are connected to establish a full-time and multi-dimensional digital construction quality evaluation model. This study is verified by a database created from the digital monitoring data of pavement construction collected from a highway construction project. The system proposed in this study can accurately reflect the quality of pavement digital construction and solve the lag problem existing in the feedback of construction site.

The increasing complexity of building projects, with high quality standards, integrated technologies and strong management restrictions, demands the intervention of numerous and diverse specialists. This requires an intense leadership, organization and coordination effort. However, building regulations, such as the Spanish Law on Building Management (LOE) 38/1999, only formally consider developers, project designers, project and work supervisors, quality control entities, construction companies, owners and final users as building agents. However, these categories are insufficient to represent the interests of all the stakeholders. The purpose of this paper is to carry out an analysis of the agents that are currently part of the entire building process. If their relationship of influence and dependence, as well as their alignment with the overall objectives of the project are studied, potential convergences, divergences, agreements and disagreements can be established. To do this, the authors conducted a prospective analysis through the MACTOR (Matrix of Alliances and Conflicts: Tactics, Objectives and Recommendations) strategic planning simulation tool, for which the rules of the Delphi technique were applied and a consultation with technical experts, both professionals and academics, was held. The research provides insight to assess the power relationships between the building agents, as well as to measure the alignment of objectives with their interests. Results show that, in the context of integrated project management (IPM), the influence of technical agents is reduced by limiting their functions to those marked by their regulatory framework, allowing them to focus on their legal powers, and the room for manoeuvre of the professional agents, who are subject to systematized monitoring and control, is also reduced. The prospective analysis also highlights the importance of defining the scope from its early stages, as well as the need to reach multilateral agreements based on the other two main constraints: time and cost.

Currently, multi-attribute auctions are becoming widespread awarding mechanisms for contracts in construction, and in these auctions, criteria other than price are taken into account for ranking bidder proposals. Therefore, being the lowest-price bidder is no longer a guarantee of being awarded, thus increasing the importance of measuring any bidder’s performance when not only the first position (lowest price) matters. Modeling position performance allows a tender manager to calculate the probability curves related to the more likely positions to be occupied by any bidder who enters a competitive auction irrespective of the actual number of future participating bidders. This paper details a practical methodology based on simple statistical calculations for modeling the performance of a single bidder or a group of bidders, constituting a useful resource for analyzing one’s own success while benchmarking potential bidding competitors.

Scope management allows project managers to react when a project underperforms regarding schedule, budget, and/or quality at the execution stage. Scope management can also minimize project changes and budget omissions, as well as improve the accuracy of project cost estimates and risk responses. For scope management to be effective, though, it needs to rely on a robust work breakdown structure (WBS). A robust WBS hierarchically and faithfully reflects all project tasks and work packages so that projects are easier to manage. If done properly, the WBS also allows meeting the project objectives while delivering the project on time, on budget, and with the required quality. This paper analyzes whether the integration of a cost breakdown structure (CBS) can lead to the generation of more robust WBSs in construction projects. Over the last years, some international organizations have standardized and harmonized different cost classification systems (e.g., ISO 12006-2, ISO 81346-12, OmniClass, CoClass, UniClass). These cost databases have also been introduced into building information modeling (BIM) frameworks. We hypothesize that in BIM environments, if these CBSs are used to generate the project WBS, several advantages are gained such as sharper project definition. This enhanced project definition reduces project contradictions at both planning and execution stages, anticipates potential schedule and budget deviations, improves resource allocation, and overall it allows a better response to potential project risks. The hypothesis that the use of CBSs can generate more robust WBSs is tested by the response analysis of a questionnaire survey distributed among construction practitioners and project managers. By means of structural equation modeling (SEM), the correlation (agreement) and perception differences between two 250-respondent subsamples (technical project staff vs. project management staff) are also discussed. Results of this research support the use of CBSs by construction professionals as a basis to generate WBSs for enhanced project management (PM).

Most construction managers use deterministic scheduling techniques to plan construction projects and estimate their duration. However, deterministic techniques are known to underestimate the project duration. Alternative methods, such as Stochastic Network Analysis, have rarely been adopted in practical contexts as they are commonly computer-intensive, require extensive historical information, have limited contextual/local validity and/or require skills most practitioners have not been trained for. In this paper, we propose some mathematical expressions to approximate the average and the standard deviation of a project duration from basic deterministic schedule information. The expressions’ performance is successfully tested in a 4100-network dataset with varied activity durations and activity durations variability. Calculations are quite straightforward and can be implemented manually. Furthermore, unlike the Project Evaluation and Review Technique (PERT), they allow drawing inferences about the probability of project duration in the presence of several critical and subcritical paths with minimal additional calculation.

This paper proposes the use of the Lego® Serious Play® (LSP) methodology as a facilitating tool for the introduction of competences for Industrial Risk Prevention by engineering students from the industrial branch (electrical, electronic, mechanical and technological engineering), presenting the results obtained in the Universities of Cadiz and Seville in the academic years 2017−2019. Current Spanish legislation does not reserve any special legal attribution, nor does it require specific competence in occupational risk prevention for the regulated profession of a technical industrial engineer (Order CIN 351:2009), and only does so in a generic way for that of an industrial engineer (Order CIN 311:2009). However, these universities consider the training in occupational health and safety for these future graduates as an essential objective in order to develop them for their careers in the industry. The approach is based on a series of challenges proposed (risk assessments, safety inspections, accident investigations and fire protection measures, among others), thanks to the use of “gamification” dynamics with Lego® Serious Play®. In order to carry the training out, a set of specific variables (industrial sector, legal and regulatory framework, business organization and production system), and transversal ones (leadership, teamwork, critical thinking and communication), are incorporated. Through group models, it is possible to identify dangerous situations, establish causes, share and discuss alternative proposals and analyze the economic, environmental and organizational impact of the technical solutions studied, as well as take the appropriate decisions, in a creative, stimulating, inclusive and innovative context. In this way, the theoretical knowledge which is acquired is applied to improve safety and health at work and foster the prevention of occupational risks, promoting the commitment, effort, motivation and proactive participation of the student teams.

This paper examines the effects of different factors on the success or failure of bids for infrastructure projects in Australia. Logistic regression analysis was used to empirically determine which factors have the largest effect on bid­ding success. Data was collected from 123 bids submitted by several infrastructure companies with subsidiaries in Aus­tralia. The analysis found that having a competitive advantage and a local partner, and also not competing against a local company were the most important factors; as they significantly increase the chances of success. However, four other factors, having relevant expertise, resource availability, a previous relationship with the client, and a previous relation­ship with consortium members, are ‘essential’ to be able to compete; as the absence of any of these four factors results in bid failure, although having them is not a guarantee of success. Results of this paper provide valuable information for any company considering the opportunity of entering into Australia’s infrastructure market as well as for companies that are already present in that country and are considering whether to bid for a specific project.

Recent catastrophes that occurred during seismic events suggest the importance of developing new seismic-resistant materials for use in building construction. Ordinary concrete is one of the most common materials in buildings. However, due to its low ductility and flexural strength, its seismic behavior can be improved upon by different additives. In this regard, wood-concrete composites exhibit desirable structural properties not achievable by either wood or concrete alone, making it an interesting material from a seismic point of view. This work analyzes and compares the performance of blocks built with ordinary concrete versus blocks built using different wood additives (sawdust and wood shavings). This includes the construction of concrete blocks in a lab, determination of their construction and seismic-resistant properties, as well as an analysis of their performance in buildings with a different number of storeys. The results show how blocks with wood aggregates comply with current regulations for structural materials in a seismic country like Chile, while also considerably outperforming traditional concrete blocks in the event of an earthquake.

Research in Bid Tender Forecasting Models (BTFM) has been in progress since the 1950s. None of the developed models were easy-to-use tools for effective use by bidding practitioners because the advanced mathematical apparatus and massive data inputs required. This scenario began to change in 2012 with the development of the Smartbid BTFM, a quite simple model that presents a series of graphs that enables any project manager to study competitors using a relatively short historical tender dataset. However, despite the advantages of this new model, so far, it is still necessary to study all the auction participants as an indivisible group; that is, the original BTFM was not devised for analyzing the behavior of a single bidding competitor or a subgroup of them. The present paper tries to solve that flaw and presents a stand-alone methodology useful for estimating future competitors’ bidding behaviors separately.

ABSTRACT Objective: To learn the profile and activities carried out by the Hospital Nurse Liaison for the continuity of care in Primary Health Care in Spain. Method: An exploratory study with a qualitative approach developed in five University Hospitals in Madrid and three in Barcelona, with Hospital Nurse Liaisons who work in Hospitals in Madrid (8) and Barcelona (11). An online questionnaire was applied with open and closed questions for data collection. The data were analyzed by the content analysis technique in the thematic modality. Results: Nineteen (19) Hospital Nurse Liaisons participated in the study. The liaisons’ ages ranged from 26 to 64 years old, the majority were women (94.73%) with experience between 21 and 30 years (52.63%), and had worked in this job between 6 months and 26 years. The Nurse Liasion is required to perform a clinical assessment of the patient prior to discharge and to contact the Nurse in the patient’s area of origin by telephone or e-mail. It is necessary to have experience as an educator, to work in a team and have motivation. Conclusion: Nurses in Spain perform care continuity for Primary Health Care, in which their activities encompass the availability of resources and experience in managing the care of complex patients and their families.

• Different types of environmental regulations have differing effects on green technology innovation efficiency (GTIE). • The relationship between command-and-control regulations and GTIE is U-shaped and there is some time lag. • The relationship between market-based regulations and GTIE is inverted U-shaped and very significant. • There is a negative linear relationship between voluntary regulations and GTIE, but only affect the current period. In the current environmentally constrained context, deploying effective environmental regulations (ERs) to promote greener technologies is necessary. Green technology innovation efficiency (GTIE) reflects the efficiency of an industry's use of resources in the green technology innovation process. However, previous research has considered innovation as a black box regarding the potential contribution and diversity of ERs. In order to analyze the differential impacts of ERs on GTIE, this study classifies ERs into command-and-control, market-based and voluntary. By adopting China's 2000–2017 construction industry as a case study, this study analyzes GTIE evolution based on a network Epsilon Based Measure (EBM) model and analyze the impacts of ERs by Tobit Regression. Findings suggest that: (1) There is a significant disconnection between the Research & Development (R&D) and commercial application stages of green technology in construction industry. The construction industry is able to turn most R&D achievements into profits at the commercialization stage, but a large amount of R&D investment does not produce R&D achievements. (2) Different types of ERs have different impacts on GTIE, but their intended outcomes can only be achieved by a suitable combination of them. [ABSTRACT FROM AUTHOR]

• Accelerating the adoption of green innovation is beneficial for an urban economy. • Command-and-control environmental regulations neither stimulate nor inhibit green innovation in Xi'an. • Market-based and voluntary environmental regulations effectively stimulate urban green innovation. • There is an inverted U relationship between environmental regulation and green innovation efficiency. While balancing economic progress and environmental pollution, environmental regulation plays a vital role conditioning green innovation. However, most research focuses on the effect of such regulations at the industry- or regional-level, lacking city-level analysis. Using the city of Xi'an (China) as a case study, environmental regulations and their effect on urban green innovation are analysed. First, using a slacks-based measure of directional distance functions (SBM-DDF) model we measure the green innovation efficiency of Xi'an from 2003 to 2016. Regression analysis is then used to explore the green innovation effect under the implementation of three environmental regulations, including command-and-control, market-based, and voluntary. Results indicate that market-based and voluntary regulations are more efficient at stimulating green innovation than command-and-control environmental regulations. The environmental regulations and green innovation efficiency also have non-linear inverted U-shape relationships. The findings will help policy makers to design more effective environmental regulations. [ABSTRACT FROM AUTHOR]

To increase the speed and efficiency of expressways construction, information management is being gradually introduced into the construction process. However, progress is limited due to the complexity of expressway engineering and application limitations of information technology. Design and delivery are still dominated by paper files, and the management of test and inspection data is still relatively extensive. Research to date into digital expressway construction has been piecemeal and fragmented with a lack of research related to the whole construction process and a data-centric information management system yet to be realized. In response, through literature research and semi-structured interviews, the framework of a data-driven digital whole-process highway construction management platform was determined. A whole process management platform was established according to the framework, and the functional application of the proposed platform was explained through a case. The framework is proposed from the perspective of the whole process of collaborative sharing., which provides a new way of thinking to solve the problems existing in the current field of expressway construction whole-process management. It also provides data-centric management, electronic design and delivery, a refined workflow, and an efficient management process., Competing Interests: Q-CN was employed by the Huaxi Company Build Installation Group Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Chen, Zhang, Ni, Skitmore, Ballesteros-Pérez, Ke, Zuo and Sun.)

Recent catastrophes that occurred during seismic events suggest the importance of developing new seismic-resistant materials for use in building construction. Ordinary concrete is one of the most common materials in buildings. However, due to its low ductility and flexural strength, its seismic behavior can be improved upon by different additives. In this regard, wood-concrete composites exhibit desirable structural properties not achievable by either wood or concrete alone, making it an interesting material from a seismic point of view. This work analyzes and compares the performance of blocks built with ordinary concrete versus blocks built using different wood additives (sawdust and wood shavings). This includes the construction of concrete blocks in a lab, determination of their construction and seismic-resistant properties, as well as an analysis of their performance in buildings with a different number of storeys. The results show how blocks with wood aggregates comply with current regulations for structural materials in a seismic country like Chile, while also considerably outperforming traditional concrete blocks in the event of an earthquake.