Blockchain-enabled Smart Contract System for Creating System-based Trust in Subcontracting Process

(Georgia Institute of Technology, 2023-03-27) Yoon, Jong Han

The unethical practices of bid shopping and peddling during the subcontractor procurement process can reduce trust between the general contractor (GC) and subcontractors (Subs) and lead to low-quality work, claims and disputes, schedule delays, and cost overruns. Despite the adverse impacts of these unethical practices on construction projects, the construction industry still lacks an ethical and trustworthy subcontracting process to prevent bid shopping and peddling. Furthermore, the transactional relationships between the GC and Subs in construction projects make profit-driven pursuits tempting, thereby increasing opportunistic behaviors. This dissertation contributes to the body of knowledge by developing a framework based on a blockchain-enabled smart contract system to address these unethical practices, thus establishing the subcontracting process grounded on system-based trust. Blockchain provides tamper-proof and decentralized data storage, and smart contracts enable an automatic contract execution by leveraging the data stored in Blockchain. The proposed framework employing the above advantages is demonstrated through a pilot test, and its feasibility and effectiveness are validated through a survey with nine professionals who had sufficient years of experience in the construction industry. The validation results show that the framework can prevent the aforementioned unethical practices and enable Subs to fairly compete for bid awards with proper budgets. In addition to the development of a subcontracting process leveraging a blockchain-enabled smart contract system, this dissertation contributes to the body of knowledge by providing a game-theoretic framework that the GCs and Subs can use to quantify and evaluate the outcomes of their strategic behaviors (e.g., trust-driven vs profit-driven behaviors) in the subcontracting process. Game theory in the framework enables mathematically analyzing and comparing the payoffs of strategic behaviors, using Nash Equilibrium. This dissertation also contributes to the body of knowledge by empirically verifying the effects of system-based trust created by a blockchain-enabled smart contract system on GCs’ and Subs’ strategic behaviors by conducting role-playing simulations. The developed game-theoretic-framework-based analysis of the simulations demonstrates that the blockchain-enabled smart contract effectively promotes trust-driven behaviors by enhancing system-based trust, thereby leading to a win-win game for the GC and Subs in the subcontracting process. These valuable findings establish the foundation for a transformative subcontracting process that is more ethical and grounded on system-based trust. Moreover, the findings can help the construction industry deepen its understanding of the significance of trust-driven behaviors in the subcontracting process. The findings also promote the enforcement of trust-driven behaviors by enhancing system-based trust through blockchain technology.
Enhancing Organizational Transformation for Design-Build Infrastructure Projects: Design Liability, Construction Quality Assurance, and New Engineering Leadership Requirements

(Georgia Institute of Technology, 2022-07-29) Lee, Jung Hyun

Major transportation infrastructure projects have used alternative project delivery, such as design-build (DB), to streamline and expedite project delivery, transferring many roles and responsibilities from state departments of transportation (DOTs) to private actors. One challenge that state DOTs face in their major DB projects is ensuring that the DB team upholds the highest standards of design and construction quality in the integrated design and construction environment. The overarching objectives of this study are to support decision-makers in streamlining project delivery by identifying challenges related to understanding gaps between public owners' expectations and the industry's perception and suggesting recommendations to mitigate the gaps. Most specifically, this study addresses issues found in DB transportation infrastructure projects and recommends innovative solutions to overcome those issues in the following areas: (1) design liability, (2) construction quality assurance, and (3) a new engineering leadership requirement on the DB team. This study utilizes a mixed-method research methodology, combining quantitative and qualitative techniques to identify key areas of variances in the integrated DB infrastructure projects. The data in this study come from a survey and semi-structured interviews. Because of the interdisciplinary nature of the research, it is necessary to capture several viewpoints from a wide range of subject-matter experts (SMEs) from multiple domains, including design consultants, highway contractors, public owners, owner representatives, insurance and legal advisors, and construction engineering and inspection (CEI) specialists. The results show that SMEs had considerably different perceptions regarding the frequency and severity of design claim sources in the DB environment. Inconsistencies between CEI perceptions and DOT requirements for quality assurance roles and responsibilities are identified. The results also highlight that a new engineering leadership requirement on the DB team will add value to large and complex projects. This study contributes to the body of knowledge in proactive design and construction quality management by providing decision-makers insights into design liability issues and opportunities to reduce them, providing guidance on reinforcing the quality assurance program for current and future DB projects, and mitigating gaps between the DOT's expectations and the industry's perceptions. The findings of this study have important implications for future practice and offer constructive guidance on streamlining project delivery in the DB transportation infrastructure market.
Human-building interaction: Supporting students’ performance and wellbeing through built environments on campus

(Georgia Institute of Technology, 2022-05-03) Kim, Yujin

Facility management aims to ensure buildings' quality and components to support occupants in achieving their goals and objectives. Campus environments play a vital role in student success by providing supportive spaces for learning, living, resting, and socializing. However, studies about the built environment of higher education have mainly focused on the ways of learning and teaching instead of physical components, and built environments on campus and their effects on students have been little studied. This study aims to 1) propose and investigate a theoretical framework on the relationship between built environments and students’ outcomes (i.e., academic performance and wellbeing) in higher education and 2) identify the preferred physical and functional environments on campus depending on student activities. This study proposed a theoretical framework based on the socio-materiality theory to explain the complex relationship between materiality and social practice in built environments. The proposed framework was tested in three-fold. First, study 1 investigated how students’ space usage of a library changed after the COVID-19 pandemic and was related to indoor environmental features. Data were collected via survey with 66 responses in pre-pandemic and interviews with 12 students during the pandemic. One of the main findings was that, even though students used the library less during the pandemic, they expected to use it as much as pre-pandemic or even more after the pandemic. Furthermore, students required different environmental features depending on their purpose of space usage, and the physical environment cultivated a sense of belonging and community. Second, study 2 tested the restorative effect in indoor settings using an eye-tracking device. Data were collected through a true experiment with 34 students randomly assigned to biophilic vs. non-biophilic design settings. The findings indicated that biophilic design itself was not decisive to restorative effects. Students in both settings selectively looked at nature-like (natural material) and views of nature and reported restoration effects. Lastly, study 3 analyzed how multi-dimensional environments (i.e., physical and functional environments) affected students’ outcomes in dormitories. A total of 128 self-reported survey responses revealed that the physical and functional environments were related to each other and directly and indirectly affected students’ perceived learning performance and wellbeing. In conclusion, this thesis provides a theoretical framework to explain the iterative process of physical and functional environments on campus and empirical evidence of the importance of built environments for enhancing student experiences and supporting different activities, such as learning, collaborating, socializing, and resting. For this, academic leadership, building managers, and designers should actively adopt the evidence-based design approach to provide appropriate environments and support student activities.
Product Model Exchange Standards for Cast-in-Place Reinforced Concrete: Implementation Methods, Value Considerations, and Application to Design Indicators

(Georgia Institute of Technology, 2022-04-27) Garcia Bottia, Leonardo

Building Information Modeling (BIM) has changed the way information in design and construction is communicated by allowing the possibility of exchanging project models and data together. To optimize the process, standards have been developed to define what is required in each exchange and how to represent it. For several years Cast-in-Place (CIP) reinforced concrete (RC), one of the most important construction materials worldwide, has been subject to considerable efforts toward the development of its standards. However, the monolithic nature of the material and its complex supply chain makes it difficult for this development to be properly carried out. This dissertation presents the results of a study with four key aims: (1) identify how exchange standards for CIP RC fit into current engineering and construction practices, (2) develop the requirements and methods for implementation, (3) study the value considerations of implementing the standards in practice, and (4) apply the information available in exchange standards to enhance the design and construction processes through the estimation of design indicators. This research is developed in the context of the undergoing efforts of the American Concrete Institute (ACI) to develop industry-wide standards for CIP RC concrete. To map the current engineering practices and challenges regarding CIP RC model exchanges, the dissertation presents the results of an ethnographic-action study performed to allow a description of current behaviors, the acquisition of qualitative data regarding the advantages of implementing BIM standards on a practical level, and to inform of potential additional requirements for standardization. To assist the implementation of standards in practice, this dissertation presents a set of methods for implementation that adapt to current tools and practices. To study the value considerations of implementing exchange standards, the same CIP RC processes captured in the ethnographic study are reproduced using the methods developed for model exchange standards. Finally, the study presents the results of a logistic regression model developed to use the parametrized information made available through these exchanges, to estimate indicators that improve the design and construction processes. In conclusion, this research provides recommendations to further develop CIP RC modeling and exchange standards, studies how design and construction practice aligns with new CIP RC standard workflows, provides methods for implementation, and develops a model useful to predict design indicators during early stages using the valuable information embedded in CIP RC exchange standards.
Analyzing Physical Workplace and Service Management Using Natural Language Processing and Machine Learning Approaches

(Georgia Institute of Technology, 2022-04-26) Hong, Sungil

The demand for workplace flexibility has emerged according to ever-changing environments, such as sharing and gig economy, alternative work arrangement, and COVID-19. This study proposes a redefined facility management model corresponding to the changing circumstances, which provides not only space but also activity support and leisure services. Coworking space (CWS) is one of the embodiments of the model. This research aims to develop CWS management strategies for 1) user preferences in physical workplace environments and services during COVID-19 and 2) data management methods utilizing natural language processing (NLP) and machine learning techniques. Two main studies in this research address three research objectives: 1) identifying preferences for facilities and services factors in CWSs during COVID-19; 2) detecting changing preferences for factors about facilities and services during COVID-19; 3) proposing the applications of machine learning and NLP techniques and demonstrating the applicability of computational data collection and analysis methods in the physical workplace management research. First, Study I proposes a thematic categorization scheme of CWS spatial and service factors and elements. Based on the categories, a mixed-method approach was utilized for the comprehensive data analysis, including content analysis, classification, and clustering. The results show that CWS users have become sensitive to disruptive behaviors and hygienic responses to infectious diseases after the pandemic. The findings also present a need for a sense of community and various technology needs for virtual interactions. Second, Study II performed the data integration of a large computerized maintenance management system dataset of a public college campus into a single CWS building maintenance dataset to build robust machine learning-based text classification models for a small dataset. The results show the qualitative and quantitative increase in prediction performance of text classifications. Study II implies that data integration will accelerate smart facility management, including small or single buildings, by sharing public datasets. In conclusion, this research sheds light on online big data collection and analysis in physical workplace management research. It also presents how the facility management industry can apply such state-of-the-art technology in utilizing historical data to make data-driven decisions.
DISADVANTAGED BUSINESS ENTERPRISES: EFFECT OF DECERTIFICATION AND COMPETING IN THE GEORGIA TRANSPORTATION CONSTRUCTION MARKETPLACE

(Georgia Institute of Technology, 2021-04-29) Horsey, Irish L.

The U.S. Department of Transportation (DOT) allocates billions of dollars annually for transportation projects. State Departments of Transportation (SDOT) that receive federal assistance for transportation contracting must meet the requirements of the Code of Federal Regulations (CFR) Title 49: Transportation Part 26 (ECFR, 2016). This regulation ensures that all business enterprises have fair opportunities for federally funded transportation contracting. Therefore, SDOTs are mandated to develop DBE goals for participation of firms, certification of DBE firm eligibility, evaluation of their DOT-assisted contracts for compliance with goals to ensure nondiscrimination in federally assisted procurement. There are eight primary objectives for the DBE program. One of which is to assist the development of firms that can compete successfully in the marketplace outside the DBE program. The DBE program has been a source of controversy since its inception (La Noue, 2008). Research shows that both DBE and non-DBE firms have grievances with the effectiveness of the overall program. Some also believe that the program creates a dependency of its participant and that inputs of knowledge would assist with the growth and development of firms to become independent contractors outside of the program (Beliveau et al., 1991). A number of factors have been presented by prior research that hinder the growth and development of certified DBE firms with a focus on performance, internal impediments, and external impediments of the program. However, there is minimal data on the preparation of DBE firms by SDOTs and their ability to compete in the open market outside of the DBE program. There is value in a study that evaluates the DBE program to determine if it is meeting the referenced objective. This research analyzes the participants of the DBE program and factors that contribute to the decertification of firms and affect their growth and development. Evaluation of certified DBEs, decertified DBEs and program administrators on this specific program objective contributes new data to the body of knowledge. The objective of this study is to evaluate the GDOT DBE program and that of similar SDOTs to determine if the DBE program in Georgia is assisting with the development of firms to compete in the marketplace. The main contribution of this research is to identify factors that assist the growth and development of DBE construction firms who voluntarily decertify and compete independently in the open market and explore the issues of certified firms that prohibit graduation. There are three outcomes of this study that contribute to the body of knowledge: regression models, development and decertification factors, and program administrator recommendations. The results of this research reveal if the program is meeting this objective for Georgia construction transportation projects based on factors obtained from the data analysis. The findings offer improvement to policy regarding the DBE program and government contracting for construction transportation projects.
DECISION SUPPORT FRAMEWORK FOR TRANSFORMING URBAN BUILDINGS AT MULTIPLE SCALES

(Georgia Institute of Technology, 2020-04-25) Chang, Soowon

Due to the increasing population, cities are requiring more energy. Among urban elements, buildings account for about 40% of energy demands and 30% of carbon dioxide emissions globally. To address the increase of energy demands and environmental responsibility, existing buildings should be transformed into highly energy efficient forms. This research explores how to support decisions that affect performance-driven smart and resilient urban systems focusing on building renovations. The research scope covers the redevelopment of existing built forms at multiple scales. Since urban objects influence urban patterns at other scales, both individual and collective performances of buildings at larger scales should be evaluated to support proper redevelopment decisions. In addition, the transformation of existing buildings will encounter different problems and challenges at different scales in urban areas. On an individual building level, the selection of different envelope options can project the future architectural environment of buildings. On a block level, the performance will be changed along with combinations of building typologies such as land use, height, floor area, etc., and therefore changes to building typologies should be managed collectively to improve the performance. When PV are applied in buildings and hourly electricity demands are recognized, the dynamic energy flows on a community level will become complex to manage. In this respect, this research is devised to identify and address redevelopment problems at different scales: individual buildings, block, and community. On the individual building level, this research studies how to support decision-making when optimizing the selection of building envelopes by using a Genetic Algorithm (GA). Based on the findings from optimizing at each scale, an interdependence of building parameters and multiple performance is observed. Therefore, decision frameworks across multiple scales are extrapolated to support community-driven and building-driven decisions. On the block level, this research explores how existing building typologies influence multiple performance indicators in a collective manner to support reconfiguring decisions using a Bayesian Multilevel Modeling. On the community level, this study addresses how the community can optimize block boundaries for resiliently managing the energy demand and supply of groups of buildings by using K-nearest neighbors (KNN) and community clustering algorithms. This research will contribute to making appropriate decisions for investment, regulations, or guidelines when renovating physical building assets at different scales in urban areas. The research findings will consolidate theoretical understandings about the relationships between building design and construction parameters considering multiple performance indicators at multiple scales in urban areas. Since many cities are at the tipping point trying to become more resilient, increasingly focusing on sustainability, economic feasibility, and human well-being, a better understanding of the impact of built forms at multiple scales will support urban development decisions for the future smart and connected communities.
Clash Resolution Optimization based on Component and Clash Dependent Networks

(Georgia Institute of Technology, 2020-04-25) Hu, Yuqing

Effective coordination across multi-disciplines is crucial to make sure that the locations of building components meet physical and functional constraints. Building information modeling (BIM) has been increasingly applied for coordination and one of its most widely used applications is automatic clash detection. The realistic visualization function of BIM helps reduce ambiguity and expedites clash detection. However, many project participants criticize automatic clash detection, as many detected clashes are irrelevant with no significant impact on design or construction work, thereby decreasing the precision of clash results and the benefits of BIM. In addition, clash detection consists of discovering problems, but it does not entail solving these clashes. Even though some studies discussed automatic clash detection, they rarely discussed the dependence relationships between building components. However, a building is an inseparable whole, and the dependent relationships among building components propagate the impact of clashes. Relocating one object to correct one clash may result in other objects violating spatial constraints, which may directly cause new clashes or indirectly cause them through relocating other components. Therefore, figuring out the dependency among clash objects with peripheral building components is useful to optimizing clash solutions by avoiding change propagation. Algorithms are designed to automatically capture dependency relations from models to construct a component dependency network. The network is used as an input to distinguish irrelevant clashes for improving clash detection quality by analyzing the relations between clash components and the relations between clash components with their nearby components. The feasibility to harness the clash component network and graph theory are also explored to generate the clash component change list for minimizing clash change impact from a holistic perspective. In addition, this study demonstrates how to use BIM information to refine clash management, and specifically focus on designing a hybrid clash correction sequence to minimize potential iterative adjustments. The contributions of this study exist at three levels. The most straightforward contribution is that this research proposed a method to improve clash detection quality as well as to provide decision support for clash resolution, which can help project teams to focus on important clashes and improve design coordination efficiency. In addition, this research proposes a new perspective to view clashes, switching the clash management focus and inspiring researchers to focus on finding global optimal solutions for all clashes other than a single clash. The third level is that even though this research focuses on clash management, the optimization algorithms based on graph theory can be used in other interdependent systems to improve design and construction performance.
A user-centered analysis of virtual reality in design review: Comparing three-dimensional perception and presence between immersive and non-immersive environments

(Georgia Institute of Technology, 2020-01-03) Paes, Daniel

Over the last few years, the adoption of Virtual Reality (VR) solutions by the construction industry has grown rapidly worldwide. These have been developed and used for different purposes, including collaborative design review. Nonetheless, the extent to which such systems enhance the cognitive capabilities of construction professionals involved in the design review activity is still unclear. Knowledge on the cognitive benefits provided by Immersive Virtual Reality (IVR) technology is essential to elicit its usefulness and effectiveness, as well as to provide development directions. In this context, this study sought to quantitatively verify the ability of an IVR system in providing users with enhanced three-dimensional (3D) perception of a BIM (Building Information Modeling) model and greater levels of presence in the virtual environment (VE) compared to a non-immersive conventional VR system. The method compares users’ 3D perception and levels of presence between two modes of presentation (IVR vs. non-immersive VR). The study also examines the relationship between 3D perception and presence within each virtual environment. Controlling for individual factors and order effects, findings indicate that in comparison to a conventional workstation, IVR technology improves 3D perception of the architectural model and provides more immersive experiences. Results also suggest no association between 3D perception and presence in virtual environments, contrary to expectations. The ability of IVR technology in providing current and future workforce with a significantly better understanding of the three-dimensional relationships of architectural models and greater levels of presence in the review task is expected to benefit collaborative design review.
Decision support system for the integration of sustainable parameters in single-family housing project delivery

(Georgia Institute of Technology, 2019-07-26) Tijo, Silvia Juliana

The implementation of sustainable practices in building construction has a direct impact on the financial, environmental, and social dimensions of sustainable development. Powering and heating buildings consumes enormous amounts of energy, and the residential and commercial building sector remains the largest end-use sector for energy in the U.S. The fact that actual energy consumption of this sector is two-fifths of the total energy consumption in the United States represents a significant economic opportunity for the country. In spite of the progress in performance and affordability of sustainable technologies, materials, and systems, the residential sector is behind in adopting these in single-family homes. Several building aspects must undergo evaluation under a holistic approach to achieving the technical and economic success of the project, but the fragmentation of the industry and the required expertise level for using existing simulating tools represent a barrier for this purpose. In residential projects, the selection of design and construction parameters occurs mostly during the early stages of the pre-construction process, while the majority of the building simulation tools require information from late stages of the process. During the early stages, the designer cannot easily predict the impact of decisions on building performance and cost. Furthermore, existing methodologies do not integrate project goals in early stages (i.e., pre-design, conceptual design, and schematic design) of the pre-construction process. Without these methodologies, selecting sustainable parameters for housing delivery and implementing sustainable principles is difficult, and consequently jeopardizes reaching sustainable goals for the building. The result of this research is a decision support system (DSS) that uses the analytic hierarchy process (AHP) and system dynamics (SD) to assist decision makers in the selection of construction parameters for sustainable housing. The proposed DSS integrates a set of project goals in the process of selecting alternatives, allowing a balance between the preferences of the decision maker and the solution that better fits those preferences. The approach focuses more on using DSS to support design exploration rather than finding optimal solutions. Given the iterative nature of the design process and the fragmentation of the construction industry, the proposed DSS provides information about costs, duration, and environmental impact of the alternatives at early stages of the project development. Therefore, an objective comparison of different design alternatives under identical conditions can take place, and the decision maker can learn from the effects of new decisions over other parameters that are interrelated. The outcomes of the research can help developers, architects, and home-owners to define sustainable parameters at early stages of the project delivery when the impact of their decisions is higher, and the cost of implementing changes is lower than in the later stages.