Despite global initiatives promoting sustainability in road construction, the asphalt paving sector encounters challenges in adopting innovative solutions. To better understand which and how barriers hinder the implementation of sustainable innovation, this study perceives the sector as a connected system. To understand how barriers are embedded in a connected system and how this is perceived differently across actor groups, we apply Total Interpretive Structural Modeling (TISM) from a Multi-Actor Perspective (MaP). Using TISM, we develop a hierarchical structure of sustainable innovation barriers and cluster them, first for the entire sector, and then for different actor groups: government, market and third-sector. This approach allows for a more nuanced examination of how barriers are perceived by different actor groups in the innovation system. The analysis reveals that a lack of trust and information exchange are high-level barriers hindering the implementation of sustainable engineering solutions. Addressing linking barriers, such as a lack of knowledge, system monitoring, and access to testing locations, can simultaneously alleviate multiple hurdles because of the barriers' interconnectedness. By combining TISM with MaP, this study moves beyond traditional innovation analyses to reveal how barriers are embedded within a broader system and how actor-specific perceptions shape the implementation landscape. In doing so, it offers a more comprehensive understanding of systemic misalignments and identifies entry points for coordinated action toward sustainable innovation.

Recognizing that sustainability transitions are often impeded by complex social and institutional factors, this study aims to identify systemic barriers that hinder the scaling up of sustainable innovations in the Dutch asphalt paving sector and the causal dynamics that shape these barriers. Using a single-case study approach, we develop a causal loop diagram (CLD) based on data from 19 semi-structured interviews with key actors, selected through snowball sampling. Through this analysis, we identified three key clusters of systemic barriers: 1) project-centric loops, reflecting the dominant project-focused perspective in business models in the sector; 2) conservative mindset loops, linked to the risk-averse mindset in the sector; and 3) collective knowledge-building loops, which highlight gaps in information exchange, monitoring, and knowledge sharing. Our findings show that a lack of collective knowledge is a core barrier, manifesting in interconnected challenges such as misinformed policies and requirements. We propose practical interventions, including mandating environmental cost indicators, developing testing lanes, supporting independent testing organizations, and creating specialized innovation roles. This study provides actionable insights for public organizations, market parties, and third-sector actors to manage infrastructure projects in ways that promote alignment with long-term sustainability goals.

Choosing by advantages (CbyA) is increasingly used in multicriteria decision contexts to anchor group decisions to facts and ensure sound decision processes. However, limitations may arise in highly uncertain decision contexts that require extensive expert knowledge. For example, in the adoption of innovative technologies to ensure safety, decision-makers are challenged by the complexity and variety of information regarding novel technologies that they can mobilize to avoid major safety hazards. To overcome this problem, we propose extending the CbyA decision-making model with a case-based reasoning expert system that captures encoded technical expert knowledge. Using design science, we empirically investigated the use of this extended model in a case where safety engineers jointly review and select an innovative pipeline safety technology. We used interviews and reviewed the technological innovation literature to define the decision problem and relevant decision factors for this case. In subsequent design iterations, we created a prototype system and validated it through three rounds of user workshops. The designed prototype guides the selection of effective technologies and anchors this selection to the implementation advantages of the technologies. By prescribing a sequence of decision steps, this study further complements the innovation literature with a procedural model that guides innovation adoption decisions in practice. The proposed model is the first step in automating CbyA decision-making, thereby indicating how the integration of expert systems facilitates complex group decisions. This study encourages broader use of CbyA in highly uncertain contexts by demonstrating the applicability of this new decision paradigm.

Previous research indicates that the presence of a champion in an innovation project increases the likelihood that firms will allocate resources to the innovation project. Relatively little is, however, known about how champions’ presence exactly influences resource allocation. A case study of two innovation projects in the construction industry was conducted to further explore this question. The findings suggest that it is not so much champions’ presence as such, but one of champions’ prototypical behaviours that influences firms’ willingness to allocate resources. Here we refer to champions’ expression of enthusiasm and confidence about the success of an innovation. Further, the findings suggests that the effect might be explained by the mediating role of firms’ expectations of the rate of adoption. Overall, the case study provides a step towards a deeper understanding of how champions induce firms to allocate resources to innovation projects.

The potential impact of emerging technologies is challenging for construction management researchers to study, as these technologies have yet to become embedded in current organisational practices. Cultural-Historical Activity Theory (CHAT) offers a method called formative interventions that may assist in this challenge. However, existing formative intervention methods are not adequately tailored to the study of emerging technologies, necessitating a more immersive engagement of the researcher-interventionist. This article proposes a renewed participatory take on the role of the researcher-interventionist and outlines the actions that researchers can undertake to investigate the future impacts of emerging technology. Specifically, we describe the interventionist role through a study of utility detection activities in which we intervened with emerging Ground Penetrating Radar (GPR) technology at twelve construction sites. We analysed our role through an inductive coding approach using interviews and field visit data. Our findings reveal five interventionist action types for intervention studies with emerging technology. These include shaping conditions, exposing tensions, supporting problem resolution, operating tools, and facilitating reflection. The action types prompted subjects to reevaluate elements of the activity system and helped describe three potential future activity systems that integrated GPR as a new tool. These findings demonstrate that a participatory take on formative interventions provides a potent means to unveil possible activity systems incorporating emerging technologies. We contribute five formal intervention action types to the literature that equip interventionist researchers with methodological tools to use CHAT in a practice-based study of emerging technologies on construction sites.

This dataset provides a comprehensive compilation of Ground Penetrating Radar (GPR) surveys across 125 utility surveying activities in the Netherlands. The dataset details the specific use of GPR in each authentic real-life utility surveying activity, whether employed independently or as a complementary tool alongside existing surveying methods, with or without post-processing. The dataset includes 959 radargrams, ground-truth information obtained from trial trenches, and an inventory of construction, geophysical, infrastructural, and technical features. The GPR utilised in all activities is an air-coupled radar with a 500 MHz frequency antenna, a GNSS RTK positioning system, and a measuring wheel encoder. This ground-truth dataset provides researchers with a valuable resource to further assess the practical efficacy of GPR as a utility surveying method, refine radargram processing algorithms and techniques, and explore the possibilities of predictive modelling.

Digital Twin-based Instructor Support System for Excavator Training Faridaddin Vahdatikhaki, Leon olde Scholtenhuis, Andre Doree Pages 521-528 (2024 Proceedings of the 41st ISARC, Lille, France, ISBN 978-0-6458322-1-1, ISSN 2413-5844) Abstract: Given the severity and magnitude of accidents caused by excavators all over the world, the training of excavator operators plays an important role in ensuring the safety of construction operations. New training modes, such as Virtual Reality-based (VR) training simulators, have started to transform training in the construction industry. Although these new developments have been proven to be very effective, it is unanimously agreed by instructors that they do not substitute on-equipment training. During the on-equipment training, an instructor needs to monitor several novice trainees and provide feedback to ensure a safe learning environment. However, being outside the cabin, having to focus on multiple trainees at the same time, and having to stay at a safe distance, instructors are very susceptible to missing important details about the performance of the students. This oversight, in the long term, can result in the institutionalization of wrong behavior in the trainees, which is then very difficult to unlearn. To this end, this research proposes a comprehensive instructor support system that utilizes a digital twining approach to help instructors circumvent the limitations of traditional training. A prototype is used in a case study to indicate the potential of the proposed approach. It is shown that the proposed system offers great potential in supporting instructors to provide more in-depth feedback to the trainees. Keywords: Digital Twin, Excavator, Training, Support System DOI: https://doi.org/10.22260/ISARC2024/0068 Download fulltext Download BibTex Download Endnote (RIS) TeX Import to Mendeley

International climate agreements and government policies, push the road construction industry towards more sustainable practices using alternative materials, new production techniques, and more efficient construction processes. Despite the broad availability of these sustainable solutions, their adoption is slow and uncertain. The reasons behind this remain unclear. This study employs a system innovation perspective to analyze the process that leads to the implementation of sustainable innovations in the Dutch asphalt paving sector. By exploring actors' roles and their interactions at different stages of the process, we aim to identify key aspects influencing the pace and outcome of the innovation implementation process in the industry. The results highlight that (1) the asphalt paving sector is anchored in a project perspective that often overlooks long-term sustainability goals, (2) several key innovation roles are not fully fulfilled, and the absence of a coordinating role is leading to misunderstandings, and (3) monitoring at both the project and sector levels is lacking; there is no holistic assessment of the overall impact of innovations. Overall, the findings suggest that sustainable innovation processes in Dutch asphalt paving remain confined to the niche level, which can be overcome by redistributing actors' responsibilities, addressing the lack of system monitoring, and overcoming the project perspective could help address the challenges in the process.

Temperature is the main driver of bridge response. It is continuously applied and may have complex distributions across the bridge. Daily temperature loads force bridges to undergo deformations that are larger than or equal to peak-to-peak traffic loads. Bridge thermal response must therefore be accounted for when performing load rating and condition assessment. This study assesses the importance of characterizing bridge thermal response and separating it from traffic-induced response. Numerical replicas (i.e., fine element models) of a steel girder bridge are generated to validate the proposed methodology. Firstly, a variety of temperature distribution scenarios, such as those resulting from extreme weather conditions due to climate change, are modelled. Then, nominal traffic load scenarios are simulated, and bridge response is characterized. Finally, damage is modelled as a reduction in material stiffness due to corrosion. Bridge response to applied traffic load is different before and after the introduction of damage; however, it can only be correctly quantified when the bridge thermal response is accurately accounted for. The study emphasizes the importance of accounting for distributed temperature loads and characterizing bridge thermal response, which are important factors to consider both in bridge design and condition assessment.

Inland navigation structures (INS) facilitate transportation of goods in rivers and canals. Transportation of goods over waterways is more energy efficient than on roads and railways. INS, similar to other civil structures, are aging and require frequent condition assessment and maintenance. Countries, in which INS are important to their economies, such as the Netherlands and the United States, allocate significant budgets for maintenance and renovation of exiting INS, as well as for building new structures. Timely maintenance and early detection of a change to material or geometric properties (i.e., damage) can be supported with the structural health monitoring (SHM), in which monitored data, such as load, structural response, environmental actions, are analyzed. Huge scientific efforts are realized in bridge SHM, but when it comes to SHM of INS, the efforts are significantly lower. Therefore, the SHM community has opportunities to develop new solutions for SHM of INS and convince asset owners of their benefits. This review article, first, articulates the need to keep INS safe to use and fit for purpose, and the challenges associated with it. Second, it defines and reviews sensors, sensing technologies, and approaches for SHM of INS. Then, INS and their components, including structures in ports, are identified, described, and illustrated, and their monitoring efforts are reviewed. Finally, the review article emphasizes the added value of SHM systems for INS, concludes on the current achievements, and proposes future trajectories for SHM of INS and ports.

Coupling asphalt construction process quality into product quality using data-driven methods Qinshuo Shen, Faridaddin Vahdatikhaki, Seirgei Miller, Andre Doree Pages 349-356 (2023 Proceedings of the 40th ISARC, Chennai, India, ISBN 978-0-6458322-0-4, ISSN 2413-5844) Abstract: The long-term quality of the asphalt layer is crucial for maintaining the functionality of roads. Despite extensive research on predicting pavement failure modes and the effect of design and road use on the quality of the asphalt layer, there is limited understanding of how the quality of road construction impacts the long-term quality of asphalt pavement. This paper presents a data-driven approach to studying the impact of construction process quality on the International Roughness Index (IRI) of roads. Two machine learning models (Random Forest and Gated Recurrent Unit) were compared in a case study, with the GRU model (R2 of 0.8284) outperforming the RF model (R2 of 0.5498). Results showed that construction process quality was the third most significant factor affecting IRI. Keywords: Asphalt construction, construction process quality, international roughness index (IRI), data-driven methods, regression, machine learning DOI: https://doi.org/10.22260/ISARC2023/0048 Download fulltext Download BibTex Download Endnote (RIS) TeX Import to Mendeley Presentation Video: https://youtu.be/vdBVP5kklLU

Operator Support Systems (OSSs) that support operators during highly time-critical asphalt compaction operations provide them with real-time sensory data. Nonetheless, the conventional asphalt compaction OSSs tend to cognitively overload operators with information that requires much human interpretation on the fly. To address the problem of OSSs' infobesity, the transition to a higher level of system automation that prescribes actions, i.e., prescriptive guidance, can be considered. To this end, this research aims to develop a novel compaction trajectory planning method that can be used to implement the Prescriptive Guidance mode in asphalt compaction OSSs. The proposed method analyzes the compaction and temperature profiles of the asphalt in real-time and suggests a compaction trajectory that ensures compaction efficiency and continuity. The proposed method is developed and compared to other types of asphalt compaction OSSs in two case studies. It is shown that while prescriptive asphalt compaction OSSs have a clear edge over more conventional OSSs in terms of improving compaction efficiency (i.e., more than 50% increase in compaction efficiency), there are still technology adoption and cultural issues that may affect the acceptance of this new technology in practice. The main contribution of this research is that it generates insights into (1) how to develop actionable and prescriptive compaction guidance, and (2) the interplay between the experience level of machine operators and the effectiveness of different support modes of asphalt compaction OSSs.

Improper design of construction equipment operator support systems can lead to the erosion of operators’ trust and ultimately failedadoption. Becausekeeping the end users in the development process is time-consuming and costly, this is seldom done. To address this issue, a new virtual reality-based framework is proposed in this study. In this framework, designers of the operator guidance system utilize a Virtual Prototyping (VP) platform of the guidance system to receive feedback from the end-users. VP platform allows end-users to have an immersive experience with the front-end system and provide feedback without requiring the designers to make a substantial investment in the design of the back-end structure. This framework is applied to a case of a compaction guidance system. It is demonstrated that VR simulators are able to serve as a technology assessment platform that allows end-users to open transparent and substantive dialogues about the system with the designers.

A framework for a comprehensive mobile data acquisition setting for the assessment of Urban Heat Island phenomenon Monic Pena Acosta, Faridaddin Vahdatikhaki, Joao Santos and André Dorée Pages 1-8 (2022 Proceedings of the 39th ISARC, Bogotá, Colombia, ISBN 978-952-69524-2-0, ISSN 2413-5844) Abstract: The debates around the Urban Heat Island phenomenon (UHI) have gained momentum in the context of smart cities and sustainable development. It is crucial to understand the complex interaction between urban features and temperature variation in the city based on reliable and detailed data. Yet, the complex interaction between the UHI of the canopy layer, paved surfaces and urban geometries (e.g., buildings, vegetation, and urban elements) has not been intensively explored to accurately capture their interplay. This is mainly caused by the palpable absence of comprehensive data that can support this type of correlational analysis. This paper proposes a comprehensive data acquisition framework to guide the collection of the requited data for the development of a data-driven UHI assessment model, with a specific focus on the contributions of paved roads to UHI. The framework was tested with a case study in Apeldoorn, the Netherlands, during a period of six months. The data collected, highlights the useability of the proposed framework for collecting high-resolution urban data required to assist local governments and urban planners to make informed decisions. To the best of authors' knowledge, this is the first time the interplay between urban feature, surface and air temperatures has been measured via mobile transects. Keywords: Data-driven methods; data collection; smart and sustainable cities; mobile sensing systems; urban heat island DOI: https://doi.org/10.22260/ISARC2022/0003 Download fulltext Download BibTex Download Endnote (RIS) TeX Import to Mendeley

Stimulating innovation through public procurement can lead to improved performance, contribute to organizational and policy goals, but can also play a key role in addressing societal challenges that cannot be adequately addressed by conventional solutions. A significant amount of research has been carried out on stimulating innovation through the public procurement of goods and services. However, there is still a lack of knowledge on which procurement strategies and tendering methods can be effectively used to encourage specific types of innovation within larger public initiatives such as civil engineering projects and programmes. The aim of this study is therefore to provide a coherent overview of innovation-encouraging procurement strategies and tendering methods, and to relate their potential effective use to the technology readiness of the targeted innovations, the required level of cooperation between public client and contractor and the willingness of public clients to bear innovation risks, and to provide incentives, budget and solution space for these innovations. Based on a literature review and a multiple case study, an innovation-encouraging procurement typology is developed. In addition, a guideline is provided that can be used by public clients to select an appropriate procurement strategy for their innovation projects and programmes.

On-equipment and practical sessions are indispensable part of construction equipment training. Currently, however, instructors receive very little to no technological support during these practical sessions, where they have to observe and provide feedback to multiple trainees concurrently. Therefore, the objective of this research is to develop a virtual Feedback Support System that can support instructors/trainees in providing/receiving feedback. This system captures the performance of trainees, translates it into a virtual model, and automatically identifies points of attention for the instructors. Instructors and trainees can use this system to communicate in a more unambiguous and objective manner. A working prototype is developed and tested in a case study at a construction training school. The usability validation session with the end-users showed that the developed system has the potential to support both trainees and instructors during the practical on-equipment sessions.

A vast amount of investment in infrastructure is required to respond to short- and long-term social, technological, and environmental needs and developments. Because infrastructure systems are highly interconnected, much can be gained by considering these interdependencies when planning future investments. However, identifying opportunities that arise from these infrastructure interdependencies has mainly been neglected. So far, the risk perspective has dominated interdependency studies. Alternatively, this paper proposes an agent-based modeling approach supporting infrastructure decision makers (1) to reveal the effects of planned sector-specific investments on the performance of interdependent infrastructures; and (2) to identify situations around which cross-sectoral coordination and collaboration can be shaped. The selected modeling approach treats infrastructure as sociotechnical systems, incorporating sector-driven operational decisions and infrastructure demand changes. They included operational decisions that respond to temporary or longer-term demand-capacity mismatch to account for the flexibility in exploiting available systemwide capacities. This modeling approach results in a more realistic estimation of infrastructure performance and beneficial co-investment opportunities. A regional transportation infrastructure system in the Netherlands is used as a case to demonstrate the approach. (C) 2022 American Society of Civil Engineers.

Integrating VR and Simulation for Enhanced Planning of Asphalt Compaction Andre Renato Revollo Dalence, Faridaddin Vahdatikhaki, Seirgei Miller and André Dorée Pages 55-62 (2022 Proceedings of the 39th ISARC, Bogotá, Colombia, ISBN 978-952-69524-2-0, ISSN 2413-5844) Abstract: The current decision-making practices in road construction, are largely based on tacit knowledge, craftsmanship, tradition, and custom. This results in considerable variability in the execution of projects and deviation between as-planned and as-executed practices. The current simulation-based planning techniques are limited because they tend to present spatial and temporal characteristics of projects separately. This segregated approach ignores the interdependencies between spatial and temporal aspects of projects specially with respect to safety and process quality assessment. This is more palpable in the asphalt compaction projects because the quality of the compaction depends on a myriad of temporal (e.g., compaction speed) and spatial (e.g., homogenous compaction of the mat) parameters. Therefore, this research aims to develop a novel framework to capture the factors affecting the compaction process in a holistic manner and translate them into relevant decision variables. This framework achieves this objective by integrating simulation and virtual reality technologies. In this framework, simulation is responsible for capturing the affecting factors and generating temporal decision variables, whereas VR virtualizes them and provides high (3D) spatial assessment and awareness. A prototype is developed and tested with ASPARi case studies to demonstrate the feasibility of the framework. It is shown that compared to current planning practices, the integrated model can significantly improve various aspects of planning the construction process, especially by improving awareness among decision-makers concerning the development of more standardized compaction patterns. Keywords: Simulation; Virtual Reality; Compaction; Planning DOI: https://doi.org/10.22260/ISARC2022/0010 Download fulltext Download BibTex Download Endnote (RIS) TeX Import to Mendeley