Large Projects Research Articles

Identifying the interests of stakeholders in large construction projects: Based on Justification theory of Boltanski and Thévenot

In large construction projects, many stakeholders are involved, often with different interests. They look at the interests through the lenses of their conflicting worldviews, leading to the formation of different worlds that often have tensions among them. For example, to be viable, the projects must find a compromise between competition and collaboration. Hence, success in developing and implementing large construction projects requires analyzing the justifications of the world of stakeholders, identifying conflicts and creating agreements among them. Thus, the main purpose of this paper is to use Boltanski and Thévenot's theory to review the justifications of stakeholders’ various and understand the tensions and compromises in large construction projects. The research approach is exploratory qualitative, realized using a multiple case study. In this process, five cases were selected as five large construction projects from the four countries of Iran, Turkey, India and Ethiopia and were analyzed based on the data extracted from written, visual, and audio sources. The results indicate that while six stakeholder groups are identified in the sources, content analysis and clear evidence reveal that the industry, construction, and market groups dominate in large construction projects. In other words, the stakeholders often justify their benefits and losses through the lens of these three worlds. In addition, the research discusses tensions and possible compromises in large construction projects. The results of this research improve the insight and knowledge of project managers and contribute to the success of large construction projects. However, it faces limitations in terms of methodology and data adequacy.

Replication study: Investigating the effects of maximal anaerobic fatigue on dynamic postural control using the Y-Balance Test

ObjectivesThe aim of this study was to replicate the study titled “Investigating the effects of maximal anaerobic fatigue on dynamic postural control using the Y-Balance Test” by Johnston et al. (2018) as part of a large replication project. This study aimed to determine the effects of maximal anaerobic fatigue on dynamic postural control using the Y-Balance Test, with a specific focus on anterior reach distance. DesignA single session intervention. MethodsForty male and female university students (age: 22 ± 3 years, height: 171.88 ± 8.96 cm, mass: 76.20 ± 14.31 kg) partaking in competitive sport, completed a Y-Balance Test protocol at 20, 10, and 0 min before a modified 60 s Wingate fatiguing protocol. Post-fatigue assessments were completed at 0, 10, and 20 min after the Wingate test. Replication outcomes included significance, direction, and effect size comparison using a z-test. ResultsA one-way repeated measures ANOVA showed a significant effect for maximal anaerobic fatigue on normalised anterior reach direction (F1.82, 69.03 = 7.16, p = 0.002, ηp2 = 0.159; 95 % CI: 0.025, 0.320). Therefore, we replicated the original findings for anterior reach distance in terms of statistical significance (F = 3.818, p = 0.025, ηp2 = 0.376; 95 % CI: 0.00, 0.62). The replication and original effect size estimates for anterior reach direction were compared using a z-test and were deemed compatible (z = 1.65, p = 0.05). ConclusionsOverall, we replicated the original study findings for the effect of maximal anaerobic fatigue on anterior reach distance in a Y-Balance Test.

An architecture for model-based and intelligent automation in DevOps

The increasing complexity of modern systems poses numerous challenges at all stages of system development and operation. Continuous software and system engineering processes, e.g., DevOps, are increasingly adopted and spread across organizations. In parallel, many leading companies have begun to apply artificial intelligence (AI) principles and techniques, including Machine Learning (ML), to improve their products. However, there is no holistic approach that can support and enhance the growing challenges of DevOps. In this paper, we propose a software architecture that provides the foundations of a model-based framework for the development of AI-augmented solutions incorporating methods and tools for continuous software and system engineering and validation. The key characteristic of the proposed architecture is that it allows leveraging the advantages of both AI/ML and Model Driven Engineering (MDE) approaches and techniques in a DevOps context. This architecture has been designed, developed and applied in the context of the European large collaborative project named AIDOaRt. In this paper, we also report on the practical evaluation of this architecture. This evaluation is based on a significant set of technical solutions implemented and applied in the context of different real industrial case studies coming from the AIDOaRt project. Moreover, we analyze the collected results and discuss them according to both architectural and technical challenges we intend to tackle with the proposed architecture.

Adjusted TextRank for keyword extraction in petrochemical project correspondence documents

A large petrochemical construction project is typically executed by multiple parties, all bound by contract agreement. During the execution phase, issues and problems may arise because the work details are not clearly specified in the contractual agreement. These issues are formally communicated and documented through written correspondence letters. By identifying important keywords within these formal letters, a comprehensive narrative of the project, including its associated issues, can be identified and analyzed. In this research, we introduce an adjusted TextRank algorithm that integrates external features from the Indonesian FastText language model and term frequency-inverse document frequency (TF-IDF) scores to identify important keywords within a dataset of correspondence letters of petrochemical projects. This enhancement involves refining phrase detection, semantic relationship estimation between words, and part-of-speech (POS) identification for words or phrases. Our results show that the proposed adjustments result in improved evaluation scores compared to the baseline standard TextRank and standard TF-IDF, respectively by 24.1% and 25% in terms of F-1 scores.

Designing for effective online Teacher Professional Development (oTPD) in building education by supporting beliefs, communities, collaboration, and development

This article reports the initial research findings from a large project on online professional development and upskilling of in-service building teachers’ digital competencies. Based on the results from a preceding literature review and the pilot delivery of the course, three key factors for the design of effective online teacher professional development in building education — beliefs, communities and collaboration, and teaching development — are exemplified and discussed. The article concludes that the pilot was successful in developing the participants’ technical skills and competencies to introduce technology in building education; however, the pilot did not significantly influence the participants’ beliefs nor made them change practice within the duration of the course.

Local social perception of mining in Parauapebas and Canaã dos Carajás in the eastern Amazonia, Brazil

The mineral industry plays a role in structural transformations in southeastern Pará, Eastern Amazonia, where large projects in this sector are located. This study analyzes aspects of the social perception of mining from image and reputation concepts in the Amazonian context. This paper aimed to examine the role of socioeconomic, political, and historical variables on social perception. It focused on four dimensions - economic, environmental, relationship and image, and general dimensions in Parauapebas and Canaã dos Carajás cities. The methodology consisted of the application in April of 2018 of questionnaires in a stratified sample of 960 and 349 randomly selected households in each of those cities, respectively. We employed the PCA/factor analysis method to examine whether a set of variables is relevant to social perception. The study found that the mining industry is a partner – not an intruder – because its beginning coincided with the social and historical formation of the territory. Perceptions of image and reputation were positive. Interviewee education, age, income, Whatsapp and Facebook usage, having a formal job, belonging to a union and a political party, occupation, and time of arrival are the main factors for social perception of mining. Despite their significantly negative opinion concerning mining's environmental impact, most interviewees pointed out that mining is reliable, friendly, transparent, and involved with the municipalities' problems. Our work fills a gap in growing literature that shows the challenges of companies, governments, and civil society in contemplating the dynamic aspects of mining for effective planning aiming at the social sustainability of mining regions.

Adopting automated bug assignment in practice — a longitudinal case study at Ericsson

[Context] The continuous inflow of bug reports is a considerable challenge in large development projects. Inspired by contemporary work on mining software repositories, we designed a prototype bug assignment solution based on machine learning in 2011-2016. The prototype evolved into an internal Ericsson product, TRR, in 2017-2018. TRR’s first bug assignment without human intervention happened in April 2019. [Objective] Our study evaluates the adoption of TRR within its industrial context at Ericsson, i.e., we provide lessons learned related to the productization of a research prototype within a company. Moreover, we investigate 1) how TRR performs in the field, 2) what value TRR provides to Ericsson, and 3) how TRR has influenced the ways of working. [Method] We conduct a preregistered industrial case study combining interviews with TRR stakeholders, minutes from sprint planning meetings, and bug-tracking data. The data analysis includes thematic analysis, descriptive statistics, and Bayesian causal analysis. [Results] TRR is now an incorporated part of the bug assignment process. Considering the abstraction levels of the telecommunications stack, high-level modules are more positive while low-level modules experienced some drawbacks. Most importantly, some bug reports directly reach low-level modules without first having passed through fundamental root-cause analysis steps at higher levels. On average, TRR automatically assigns 30% of the incoming bug reports with an accuracy of 75%. Auto-routed TRs are resolved around 21% faster within Ericsson, and TRR has saved highly seasoned engineers many hours of work. Indirect effects of adopting TRR include process improvements, process awareness, increased communication, and higher job satisfaction. [Conclusions] TRR has saved time at Ericsson, but the adoption of automated bug assignment was more intricate compared to similar endeavors reported from other companies. We primarily attribute the difference to the very large size of the organization and the complex products. Key facilitators in the successful adoption include a gradual introduction, product champions, and careful stakeholder analysis.

Automated construction scheduling using deep reinforcement learning with valid action sampling

The growing demand for buildings and infrastructures requires optimal construction schedules under real-world complexities. This paper presents an automated scheduling optimization method for large construction projects, considering real-world constraints and the need for rescheduling. A Deep Reinforcement Learning (DRL) model with a Valid Action Sampling (VAS) mechanism is proposed to optimize schedules. The method integrates a Graph Convolutional Network (GCN) for feature extraction and includes a reward shaping mechanism to expedite convergence. The proposed method outperforms traditional methods with reduced project duration and runtime in both scheduling and rescheduling cases. This advancement benefits construction managers seeking efficient and flexible project management. The findings inspire future research into broader and more practical construction scheduling solutions utilizing DRL.

Blinded like a state: Water scarcity and the quantification dilemma in Morocco

Over the last two decades, the Moroccan state has had to deal with some deeply uncomfortable knowledge regarding mounting water scarcity. This presents governing actors with a difficult dilemma. On the one hand, this knowledge is politically disturbing as it could undermine prevailing hydro-agricultural policies, which are based on the promise of unlimited irrigation expansion. It could also corrode the dominant social alliance built around these policies. On the other hand, accurately quantifying water resources has long been essential for establishing the technocratic legitimacy of the state.This paper investigates how the state manages uncomfortable numbers that it has either produced or endorsed: an issue rarely addressed by social studies of quantification, but increasingly consequential in the current ecological crisis. Drawing from a literature on the production of ignorance, we highlight contradictory processes of knowledge production and ignorance. We show that Moroccan state hydrologists have dealt with uncomfortable figures by keeping them fragmented in space and time. They have continued to produce innumerable measurements of water scarcity. However, they have done so in an increasingly scattered manner, both spatially and temporally, while studiously avoiding integrating these fragments into updated national estimates.This uneasy compromise between “seeing” and “not seeing” like a State has so far helped reproduce the “modernizing” social alliance forged around large hydraulic projects. However, its durability is doubtful. Our case study thus raises a number of hypotheses about what the ecological crisis could do to state quantification in many places and in the near future.

Governance practices of large construction projects

Governance practices of large construction projects

Measurement-induced phase transition in teleportation and wormholes

We demonstrate that some quantum teleportation protocols exhibit measurement induced phase transitions in Sachdev-Ye-Kitaev model. Namely, Kitaev-Yoshida and Gao-Jafferis-Wall protocols have a phase transition if we apply them at a large projection rate or at a large coupling rate respectively. It is well-known that at small rates they allow teleportation to happen only within a small time-window. We show that at large rates, the system goes into a new steady state, where the teleportation can be performed at any moment. In dual Jackiw-Teitelboim gravity these phase transitions correspond to the formation of an eternal traversable wormhole. In the Kitaev-Yoshida case this novel type of wormhole is supported by continuous projections.

Critical Evaluation of the Contract Selection Process Used in the Construction Industry of Kuwait

The paper investigates and assesses the contract selection procedure used in Kuwait’s construction sector. The ideas and insights of engineers involved in significant Kuwaiti construction projects will be extensively considered. In the Kuwaiti building sector, various ways of choosing the contract form will be discussed. In order to gather pertinent data about the country’s primary construction projects, questionnaires will be used. This methodology ensures a first-hand account of the challenges and preferences within the industry. This data will be analyzed to determine the best ways to enhance the current system utilized for Kuwaiti building contracts for the choice of contract forms and payment terms that could benefit from the inclusion of measures to guarantee those types of task delivery systems and payment terms in the country’s future construction projects. This paper explores the typical contract types and payment mechanisms used in Kuwait, drawing on a thorough analysis of current literature, governmental regulations, and business practices. The Standard Forms of Contract, which offer fixed-priced payments, have become the most popular option. However, when used for extensive and technically challenging projects, this contract form’s simplicity presents difficulties. Additionally, the existing system encourages contract awards based on the lowest tender, which raises questions regarding appropriateness and proportionality. The study suggests an arsenal of criteria for improving the deal selection process, with an emphasis on diverse terms of payment inside the task delivery system, in order to allay these worries. It highlights the need for a more comprehensive approach for deal selection that takes project complexity, financial constraints, and long-term project interest into account. The proposed criteria additionally include adaptability to project complexity, ensuring flexibility for challenges in large projects. Financial considerations, aligning with budgetary requirements, are crucial. The emphasis is on long-term project success, and finding a balance between simplicity and adaptability in contracts is key. These comprehensive criteria aim to improve decision-making in selecting standard contract forms for construction projects, addressing challenges in large, technically demanding endeavors in Kuwait. This research contributes to the field by introducing a novel set of criteria for contract selection, tailored to the Kuwaiti construction context. The study’s originality lies in its approach to addressing the challenges posed by current practices and its focus on refining the system for future projects. Additionally, the study employs a rigorous questionnaire survey to extract firsthand insights from industry professionals, ensuring a robust and contextually relevant exploration of the contract selection landscape in Kuwait’s construction sector.

Using Version Control Information to Visualize Developers' Knowledge

It is not always clear in case of a software project who has the right amount of knowledge concerning a certain module or file. Programmers frequently ask questions like "Who knows the most about this code?" or "Who can I ask for help when I work on this module?". In a large, long-term software product, knowledge is distributed in an uneven way among developers. Developer fluctuation during the product lifetime might cause some parts of the code to be known very well by a multitude of developers, while other parts might sink to the "gray zone", where developer competence is dangerously scarce. It is important for the project management to identify such critical points, to avoid the complete loss of competence. Version control repositories contain loads of useful information about the evolution of a software project. This paper presents a developer-centered visualization that is intended to show individual, team-bound and company-bound knowledge of large legacy projects. The competence information is computed from the extracted version control information from Git repositories. The calculated competence value is based on the number of commits per developer and their significance. Aggregated views for teams and companies are available based on various heuristics. The visualization is implemented as a new plugin in CodeCompass, a standalone, open-source code comprehension software. Project managers and individual developers may both profit from the tool, whether it concerns software evolution, human-resource management, architecture, knowledge catch-up, or blame.

Knowledge infrastructure for integrated data management and analysis supporting new approach methods in predictive toxicology and risk assessment

The EU-ToxRisk project (2016–2021) was a large European project working towards shifting toxicological testing away from animal tests, towards a toxicological assessment based on comprehensive mechanistic understanding of cause-consequence relationships of chemical adverse effects. More than 40 partners from scientific institutions, industry and regulators coordinated their work towards this goal in a six-year long programme. The breadth and variety of data and knowledge generated, presented a challenging data management landscape.Here, we describe our approach to data management as developed under EU-ToxRisk. The main building blocks of the data infrastructure are: 1) An easy-to-use, extensible data and metadata format; 2) A flexible system with protocols for data capture and sharing from the entire consortium; 3) A methods database for describing and reviewing data generation and processing protocols; 4) Data archiving using a sustainable resource; 5) Data transformation from the archive to the system that provides granular access; 6) Application Programming Interface (API) for access to individual data points; 7) Data exploration and analysis modules, based on a «web notebook» approach to executable data processing documentation; and 8) Knowledge portal that ties together all of the above and provides a collaboration space for information exchange across the consortium. This knowledge infrastructure is being extended and refined for the support of follow-up projects (RISK-HUNT3R, ASPIS cluster, European Open Science Cloud (2021–2026)).

Design Students’ Affordance-based Messages in an Undesigned Design Studio

In this study, as PhD candidates and teaching assistants working in the Interior Architecture Department of the Faculty of Architecture at Istanbul Technical University (ITU) we aimed to explore the interrelationship between the students’ messages and the studio’s affordances by using participant observation and photovoice methods in the classes we attended in the same physical space. We used the photographs taken by us during the studio courses as the central data set to explore the messages triggered by the studio affordances, which are formed based on the complex environments and relationships created by the limited physical facilities of our design studio, the high student quotas and the large project groups using the same physical space at different and even the exact times. Through collaborative commentary and reflective writing, we produced written and visual reports on the final themes at the conclusion of the analysis process. Finally, we concluded that the four main themes, namely, direct message, indirect message, transcendent message, and no message but action, guided us in exploring and explaining our studio’s affordances.

Analysis of 14,392 whole genomes reveals 3.5% of Qataris carry medically actionable variants.

Arabic populations are underrepresented in large genome projects; therefore, the frequency of clinically actionable variants among Arabs is largely unknown. Here, we investigated genetic variation in 14,392 whole genomes from the Qatar Genome Program (QGP) across the list of 78 actionable genes (v3.1) determined by the American College of Medical Genetics and Genomics (ACMG). Variants were categorized into one of the following groups: (1) Pathogenic (P), (2) Likely pathogenic (LP), and (3) Rare variants of uncertain significance with evidence of pathogenicity. For the classification, we used variant databases, effect predictors, and the disease-relevant phenotypes available for the cohort. Data on cardiovascular disease, cancer, and hypercholesterolemia allowed us to assess the disease-relevant phenotype association of rare missense variants. We identified 248 distinct variants in 50 ACMG genes that fulfilled our criteria to be included in one of the three groups affecting 1036 genotype-positive participants of the QGP cohort. The most frequent variants were in TTN, followed by RYR1 and ATP7B. The prevalence of reportable secondary findings was 3.5%. A further 46 heterozygous variants in six genes with an autosomal recessive mode of inheritance were detected in 200 individuals, accounting for an additional 1.4%. Altogether, they affect 5% of the population. Due to the high consanguinity rate in the QGP cohort (28% in spouses and 60% in parents), P and LP variants both in genes with dominant and recessive inheritance are important for developing better treatment options and preventive strategies in Qatar and the Arabic population of the Middle East.

Regional Interferences to Photovoltaic Development: A Polish Perspective

The stability of energy generation is crucial for the functioning of every country. Currently, the EU policy is moving towards becoming independent of fossil energy sources, which can be replaced with sources that are not exhaustible, for example, energy from the sun. Public awareness of renewable energy is increasing. People are willing to invest in natural solutions. However, planning large photovoltaic farm projects is difficult due to complex location requirements. The study aimed to analyse the interferences/barriers to be considered when searching for a suitable location to install a photovoltaic farm. The analysis was conducted for the territory of Poland. The study used a literature and local legislation query and the Delphi method. The Delphi method identified the most important interferences from the investor’s perspective. Eleven interferences have been identified, classified into legal, spatial, technical, social, and financial groups. Several are locally determined and only exist in selected locations (e.g., technical determinants of the power grid condition, etc.). In contrast, others are unitary (e.g., concerns about the impact of PV on human health, etc.). The decision-makers are aware of the existing interferences/barriers, and the proposed administrative, legal, and technical solutions marginally mitigate barriers. System solutions are recommended, allowing an easier way to find a suitable location for a PV system.

Sounds of the Skagit: a comprehensive noise model for a large hydroelectric project

The Skagit Hydroelectric Project comprises three dams and power plants in the North Cascades and transmission lines running from the plants to Seattle. HDR helped Seattle City Light complete numerous studies in support of relicensing of the Project. The sound study was charged with evaluating noise from all project-related activities, which include noise from the powerhouses, transmission lines, dam spill events, emergency sirens, telephone alerts, helicopter flights, boat traffic, vehicle traffic, construction equipment, and even a locomotive bell rung by visitors. Models used include Cadna-A, AEDT, and BPA's corona noise model. The sound study also included week-long measurements of existing noise at six locations during summer (peak recreation season) and spring (off-season), processed using National Park Service methods. Regular emergency siren testing allowed the model to be validated across long distances using the noise monitoring data. This presentation will discuss the varied approaches HDR's acoustics team used to synthesize all of these aspects into one award-winning sound study - this project won INCE's 2023 Nancy Timmerman Member's Choice Award.

Matrix-based project dataset parsers

There are several existing project datasets, which involve separate data sources for simulated and real projects, individual and multiprojects, and single- and multimodal attributes. In addition, their file structures are heterogeneous; therefore, scholars can usually use only one dataset to test a proposed scheduling or resource allocation algorithm. Since the internal structures of these projects are also very different, it is difficult to ensure that an algorithm optimized for a given type of project will also perform well on projects with other structures. The proposed parsing method supports researchers in:•reading several types of projects: simulated, real, individual, and multiprojects, as well as single- and multimodal attributes;•considering the priorities of activities and the flexibility of their dependencies, which is essential for modeling the structural flexibility employed by agile, hybrid, and extreme project management approaches;•building a large project database for testing and comparing different scheduling and resource allocation algorithms.

The tortoise in the urban development network: How social relations affect decision-making speed in a road expansion project in Kristiansand, Norway

ABSTRACT Why do urban development projects take a long time to complete? This question is of paramount importance, both practically and academically. Practically, understanding the reasons for delays in these projects can help improve project efficiency, reduce costs, and enhance stakeholder satisfaction. Academically, the study contributes to the field of urbanization by applying social network analysis (SNA) to explore the interactions and relationships among decision-makers in urban development projects. This study draws upon original data from a road extension project in Kristiansand to illustrate and explain why the implementation of large development projects suffers from convoluted and slow decision-making processes after an overall agreement on project aims and goals has been established. This study draws on a sample of 33 actors who participated in the decisions concerning the project. I collected the data through a combination of interviews and document reviews and subsequently analyzed them using social network structural metrics and visualization techniques. The results show that the actors are connected in less dense, more centralized, and clustered networks with subgroups and low reciprocity which have hampered efficient communication, resulting in delays. The findings imply that the pattern of relationships among decision-making actors can affect the amount of time taken to reach conclusions in urban development initiatives.