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This paper aims to identify how a public client’s use of control systems (process, output and social control) affect innovation possibilities in construction projects.

Semi-structured interviews about six infrastructure projects were conducted to identify respondents’ views on innovation possibilities. These possibilities were then analyzed from an organizational control perspective within principal–agent relationships between the Swedish Transport Administration (STA) and their contractors.

How the client uses control systems affects innovation possibilities. Relying on process control could negatively affect innovation opportunities, whereas output control could have a positive influence. In addition, social control seems to have a weak effect, as the STA appears not to use social control to facilitate joint innovation. Public clients must comply with the Public Procurement Act and, therefore, retain the requirements specified in the tendering documents. Much of the steering of the execution is connected to the ex ante phase (before signing the contract), which affects innovation possibilities in the design and execution phases for the contractor.

This study was conducted with only one client, thus limiting its generalizability. However, the findings provide an important stepping stone to further investigation into balancing control systems and creating innovation possibilities in a principal–agent relationship.

Although public procurement has increasingly been emphasized as a major potential source of innovation, studying how a public client’s use of organizational control systems affects innovation possibilities in the construction sector has received scant attention.

Prior research has emphasised the importance of the early phases of construction projects, as well as the difficulties of procuring engineering services – especially due to the uncertainties. Despite that, studies on the public procurement of engineering services are scarce. Although scholars have shown that uncertainty may affect the choice of control modes, the level of uncertainty that characterises services is not addressed by the two task characteristics: knowledge of the transformation process and output measurability. The purpose is to investigate organisational control in public procurement of engineering services.

The existing control model was adjusted in this study by conceptually adding uncertainty as a third aspect to the two task characteristics. A single case study of the Swedish Transport Administration was used. The empirical data, comprising 14 interviews with managers from the client and engineering consulting companies, were analysed using flexible pattern matching and visual mapping approaches and then illustrated using the model.

The public client did not base its choice of control modes on uncertainty, but rather on the other two task characteristics. Consequently, the service providers argued that the chosen control modes reduced their creativity, increased their financial risks and caused unclear responsibilities. This study therefore shows that uncertainty is an important factor to consider in the choice of control modes, both from a theoretical perspective and from the service providers' point of view. The developed model may therefore be useful for researchers as well as practitioners.

This study is the first attempt to add uncertainty as a task characteristic when choosing control modes. The results contribute to the scarce control literature regarding the procurement of engineering services for construction projects and the procurement of other services with high uncertainty.

The variance between the winning bid and the owner's estimated cost (OEC) is one of the construction management risks in the pre-tendering phase. The study aims to enhance the quality of the owner's estimation for predicting precisely the contract cost at the pre-tendering phase and avoiding future issues that arise through the construction phase.

This paper integrated artificial neural networks (ANN), deep neural networks (DNN) and time series (TS) techniques to estimate the ratio of a low bid to the OEC (R) for different size contracts and three types of contracts (building, electric and mechanic) accurately based on 94 contracts from King Saud University. The ANN and DNN models were evaluated using mean absolute percentage error (MAPE), mean sum square error (MSSE) and root mean sums square error (RMSSE).

The main finding is that the ANN provides high accuracy with MAPE, MSSE and RMSSE a 2.94%, 0.0015 and 0.039, respectively. The DNN's precision was high, with an RMSSE of 0.15 on average.

The owner and consultant are expected to use the study's findings to create more accuracy of the owner's estimate and decrease the difference between the owner's estimate and the lowest submitted offer for better decision-making.

This study fills the knowledge gap by developing an ANN model to handle missing TS data and forecasting the difference between a low bid and an OEC at the pre-tendering phase.

The purpose of this study is to investigate the benefits and challenges of implementing circular economy (CE), as well as shed light on the influence of procurement strategy in CE implementation in construction projects.

A qualitative research approach with abductive reasoning was adopted. The empirical data were collected from the construction industry in the United Arab Emirates (UAE).

The results reveal that clients, consultants and contractors have limited awareness, knowledge and motivation to implement CE in construction projects. The absence of incentives to design projects following CE principles, lack of involvement of contractors and suppliers, non-use of materials that use CE principles and current procurement strategies are the main challenges for the implementation of CE in the UAE.

Previous research offers limited knowledge on CE and its implementation in construction projects particularly from a procurement strategy perspective. The findings of the study provide new knowledge of the benefits, challenges and role of procurement strategy for implementing CE. It is suggested that collaborative and partnering-based procurement methods are needed to facilitate the effective implementation of CE.

The study aims to explore the role of procurement of good governance (PGG) on value for money (VfM) achievement in public construction projects. By investigating various dimensions of PGG, including transparency, accountability, competition and integrity, this study provides insights into how these factors contribute to the successful achievement of VfM outcomes in public construction projects.

The data were sourced from 203 construction project practitioners from 24 selected procuring entities in Tanzania using a census approach and a cross-sectional questionnaire survey. Confirmatory factor analysis (CFA) and structural equation modelling (SEM) were used for data analysis.

The findings of the study revealed a positive and significant impact of various dimensions of PGG on VfM. Specifically, transparency, accountability, competition and integrity were positively and significantly related to VfM, with p-values <0.001. Based on the study findings, we conclude that PGG is an important predictor of VfM achievement in public construction projects.

The study offers policy implications for streamlined PGG and VfM achievement in public construction projects. It is suggested that procuring entities can enhance VfM by enforcing compliance with the principles of PGG throughout the entirety of construction projects. In this case, streamlined legislative frameworks and control mechanisms are crucial components that could enhance PGG and the achievement of VfM.

This study contributes to the academic literature on the strategic role of PGG in enhancing VfM achievement. This is one of the research domains, which has not been adequately researched, particularly in Tanzania’s context. In addition, the study provides valuable insights to policymakers, practitioners and stakeholders involved in public construction projects to improve project outcomes and resource allocation.

The primary purpose of this study is to explore the relationship between the unsolicited proposal (USP) and the performance of private participation infrastructure (PPI) projects in developing countries.

The main data set for this study was collected from the World Bank database consisting of 8,951 PPI projects that occurred in developing countries from 1996 to 2020. Hierarchical logistic regression was applied for investigating the effects of USPs on project success. Three moderators, namely, control of corruption, presence of local sponsor and project size were also included in the model to test the impact of their interactions with the USP on the performance of PPI projects. Further, to assess the impact of the effect of USPs, the average marginal effect was calculated. The framework used in this study consists of 18 control variables, three moderators and one noncontrolled independent variable (the USP).

The results of hierarchical logistic regression indicate that USPs have a significant and negative effect on the success of PPI projects occurring in developing countries. The negative effect of a USP weakens with the presence of local sponsors and stronger control of corruption in the host country. However, contrary to the authors’ expectations, the results show that project size does not significantly affect the association between USPs and the success of PPI projects. Moreover, the results of average marginal effects show that the negative impact of USP on the success of PPI projects ranges between 2.4% and 3.8%.

This study quantifies the negative impact of USP on the success of PPI projects in developing countries, which will be helpful for the practitioners to understand the associated risk with USP projects. Furthermore, it also identifies the moderating roles of control of corruption and the presence of local sponsors on the relationship between USP and the success of PPI projects.

Infrastructure forms a basis for the operations and sustainability of the modern society. This paper aims to recognize value creation from the infrastructure procurement ecosystem perspective to achieve those goals. The pursuit of enhancing value creation involves an examination of infrastructure procurement challenges, boundaries as well as boundary spanners that facilitate effective knowledge transfer and interaction.

The qualitative study is based on content analysis of 25 thematic interviews. Data was transcribed and coded via Atlas.ti software.

Infrastructure procurement value creation challenges appear complex and related to boundaries that hamper collaboration, coordination and knowledge sharing. Our results show that these boundaries locate within and between different levels of procurement ecosystem. Therefore, value creation in infrastructure procurement requires boundary spanners for leveraging knowledge sharing and interaction. Artifacts, discussion, processes and brokers as identified boundary spanners are strongly nested and interrelated in the industry. Special attention should be given to supporting individuals to act as brokers, since they play the key roles in trust building, culture steering and usage of other boundary spanners.

Promoting value creation in infrastructure procurement helps to achieve socio-economic development goals.

This study offers a unique perspective on value creation in the context of infrastructure by adopting an ecosystem lens and examining boundary crossing mechanisms. The results support future development of collaboration and knowledge sharing practices fostering procurement productivity.

This study aims to review recent advances towards the implementation of ANN and NLP applications during the budgeting phase of the construction process. During this phase, construction companies must assess the scope of each task and map the client’s expectations to an internal database of tasks, resources and costs. Quantity surveyors carry out this assessment manually with little to no computer aid, within very austere time constraints, even though these results determine the company’s bid quality and are contractually binding.

This paper seeks to compile applications of machine learning (ML) and natural language processing in the architectural engineering and construction sector to find which methodologies can assist this assessment. The paper carries out a systematic literature review, following the preferred reporting items for systematic reviews and meta-analyses guidelines, to survey the main scientific contributions within the topic of text classification (TC) for budgeting in construction.

This work concludes that it is necessary to develop data sets that represent the variety of tasks in construction, achieve higher accuracy algorithms, widen the scope of their application and reduce the need for expert validation of the results. Although full automation is not within reach in the short term, TC algorithms can provide helpful support tools.

Given the increasing interest in ML for construction and recent developments, the findings disclosed in this paper contribute to the body of knowledge, provide a more automated perspective on budgeting in construction and break ground for further implementation of text-based ML in budgeting for construction.

By adopting the “hard” and “soft” project management (PM) approaches from the PM-literature, this paper aims to problematize the expected role of client organizations in driving innovation in the transport infrastructure sector.

Addressing a large public client in Sweden, a case study design was initially applied to provide in-depth insights and perspectives of client project managers’ views and experiences of managing projects expected to drive innovation. In this paper, the concepts of “hard” and “soft” are used to discuss empirical findings on challenges associated with adopting a PM-approach for driving innovation in projects. The empirical material consists of interview data, complemented with observations and archival data.

Findings reveal challenges associated with combining hard and soft approaches, frequently demonstrating difficulties in balancing short-term project expectations with the promotion of innovation. In line with the literature, project managers note that there is a need for soft approaches to promote development and drive innovation. Yet, findings reflect a situation in which operational success criteria predominate, whereas soft approaches are not sufficiently used to create the grounds required for fostering innovation.

Insights are provided into how PM-approaches may impact construction innovation in the infrastructure sector, demonstrating a need for further research on the challenges and implications of applying and combining hard and soft PM-approaches.

This paper aims to comprehensively analyze the factors influencing the adoption intentions of the digital rupee, a digital currency, among users in India.

Drawing upon the Technology Acceptance Model (TAM), the study examines the relationships between cognitive beliefs (perceived usefulness, perceived ease of use, perceived trust, perceived self-efficacy, perceived cost and awareness), affective belief (attitude) and adoption intention of the digital rupee. The study uses a structured questionnaire to collect primary data from 1,707 respondents, which are then analyzed using structural equation modeling.

The results indicate that perceived usefulness and perceived ease of use significantly impact users' attitudes toward the digital rupee, as well as their adoption intentions. The findings further reveal that perceived trust, perceived self-efficacy, and awareness positively influence attitude and adoption intention. On the other hand, perceived cost exhibits a negative effect on attitude and adoption intention. These results provide empirical evidence on the factors that shape users' attitudes and intentions toward adopting the digital rupee.

The research methodology used in this study ensures rigorous data collection and analysis. The structured questionnaire enabled the collection of detailed information from a large sample of respondents, allowing for robust statistical analysis. The utilization of structural equation modeling facilitated the examination of complex relationships among variables, enhancing the reliability and validity of the findings.

The study's findings offer practical guidance for policymakers, financial institutions and researchers in shaping digital currency regulatory frameworks, tailored financial services and further exploration of adoption dynamics.

The research has social implications by potentially influencing the way individuals and communities in India engage with digital currencies, impacting financial inclusion and digital economic participation.

This research contributes to the understanding of the adoption of digital currencies in India and provides valuable insights for policymakers, financial institutions and researchers in the field of digital finance and technology adoption.