Construction is unquestionably one of the largest industry contributors to any national economy. However, the sector faces significant problems with long-term performance, productivity and competitiveness; it is also very diverse and fragmented. It is generally accepted that the industry worldwide does not have a coherent model of innovation development, is unwilling to innovate, does not invest in R&D sufficiently, and shows a conservative attitude towards mass inclusion of cutting-edge technology into construction processes. The Russian construction industry is no exception. The Russian construction industry development lags far behind the world in creating and disseminating building materials and technologies. To stay competitive, Russian domestic construction companies need to continue their innovative activities, in order to exploit existing technological opportunities, despite the difficult financial climate. A high level of innovation performance is extremely important for this industry growth and for the development of the Russian economy. Innovations include the use of new building materials, machinery, and engineering equipment that increase the quality of operations and customer satisfaction (e.g. energy-efficient, soundproofing materials). They also include new, efficient construction technologies and software for architectural and construction design that enable the achievement of higher productivity, and lower construction times such as Building Information Modelling and off-site fabrication. This PhD study was founded on the innovation system approach which stresses that construction innovation is not limited by the boundary of a single construction company, but by a sectoral innovation system. In other words, the innovation performance of the industry depends not only on how individual firms perform in isolation, but on how they interact with other system actors (i.e. governments and academia) and contribute to the development and diffusion of innovations from a dynamic perspective. The theoretical framework developed for the Russian construction innovation system has a strong focus on these links between the government, industry and academia. Thus, creating a favourable environment for construction innovation is heavily dependent on government and construction companies. Moreover, construction innovation is also conditional upon the collaborative readiness of construction companies and research institutions to integrate their knowledge and expertise to maximise industry innovativeness. The overarching goal of this research was to explore the dynamic complexities inherent in construction innovation through the formulation of a system dynamics (SD) simulation model that focuses on the challenging Russian Federation context. The SD model was the outcome of a purpose-built integrated participatory systems modelling (IPSM) approach. This comprehensive IPSM approach employed and integrated various data collection techniques, including, questionnaire surveys, face-to-face interviews, direct expert consultations, empirical structural analysis, and a series of stakeholder workshops. A robustly developed SD model can help to address the challenges of transforming Russia’s construction industry into a highly developed sector by providing an understanding of how government policies and supportive programs could encourage industrialists to innovate, promote research and transfer technology. Such actions would ultimately improve industry innovativeness. The SD model sought to also understand and encapsulate the innovation dynamics of two innovation development typologies, namely, imitators and innovators. Imitators represented construction firms that introduced and implemented technological innovations by adopting and/or adapting ideas from others, in terms of improved construction materials, techniques, construction methods, products and services. Innovators represented companies that implemented technological innovations as a result of collaborative R&D. Such companies are constantly involved in R&D and implement newly introduced (i.e. subjected to significant technological changes) construction materials, techniques, goods and services based on new technologies, or on the combination of new technologies with existing ones. Overall, findings indicated that the Russian construction industry’s unwillingness to implement innovative technological advancements is primarily caused by the inability of the government to build an institutional, regulatory and legislative framework that would encourage firms to innovate. Among the key factors which hinder innovation processes are: the absence of a system of economic incentives for industrialists and research institutions; weak investment activity of construction companies due to a lack of funds; excessive administrative barriers; inappropriate technical regulation along with outdated construction norms and codes; a serious lack of research support; weak R&D collaboration between industry and academia; and conservative procurement methods. The SD model provided empirical evidence that effective strategies are required to overcome the challenges of transforming Russia’s construction industry into one which is highly innovative. The following factors might generate successful adoption of ground-breaking processes and products in the Russian construction industry: government support; client demand for innovation; access to information and knowledge for construction companies; and R&D collaboration. Hence, the number of imitators and innovators is only likely to increase if there is sufficient support for increased collaboration within the innovation system. Moreover, there is a need to improve procurement practises that would lead to increasing demand for high-quality construction goods and services. The SD model was also utilised to derive an understanding of the Russian construction industry with regards to innovation development and diffusion within the context of four plausible transition scenarios (i.e. business as usual, market forces, conservative development and innovation power). Specifically, the transition scenarios were developed by considering the variation of two important but uncertain factors driving innovation in the construction sector, namely: (1) the conditions and level of government financial support; and (2) demand for innovation related to market expectations, largely dictated by traditional versus progressive procurement processes. Simulation results under alternative scenario settings revealed that industry transformation requires sustained and coordinated innovation diffusion strategies that engage all innovation stakeholders. One key finding was that the Russian construction industry shows preference for imitation-oriented innovation development. Even though construction innovation diffused more rapidly, and seeded more innovators than imitators for the innovation power transition scenario (whereby increasing government support was coupled with extensive reductions in barriers), it would still take time to develop a sufficient proportion of truly innovative companies. The market forces and state-led conservative development transition scenarios showed similar levels of innovation outcomes within the modelling horizon, but predominately yielded innovation imitators. Lastly, the extensive scenario analysis findings culminated in the formulation of both policy and practical recommendations for enhancing innovativeness in the Russian construction sector, for overcoming its excessive conservatism, and for shaping a successful industry transition into an innovative future. In summary, this PhD thesis has made significant contributions to the theoretical, methodological and practical knowledge in the fields of construction innovation and systems modelling. The application of a systems approach to the analysis of construction innovation processes provided insights into both the complexity and inherent dynamics of innovation processes caused by multiple feedback loops, non-linearity, and time delays in decision-making. The IPSM modelling approach provides both a high degree of scientific rigour and an efficient participatory modelling procedure for building SD models. It can be used to deal with various problems where uncertainty in scientific knowledge, and lack of empirical data presents difficulties. Finally, the herein demonstrated concept of connecting a particular SD model for a particular system (i.e. construction innovation in this study) with that of macro industry transition scenarios, would be useful for government policy-makers to develop more fit-for-purpose strategies.