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Factors like bid price, submission time, and number of bidders influence the procurement process in public projects. These factors and the award criteria may impact the project’s financial compliance. Predicting budget compliance in construction projects has been traditionally challenging, but Machine Learning (ML) techniques have revolutionised estimations.

In this study, Portuguese Public Procurement Data (PPPData) was utilised as the model’s input. Notably, this dataset exhibited a substantial imbalance in the target feature. To address this issue, the study evaluated three distinct data balancing techniques: oversampling, undersampling, and the SMOTE method. Next, a comprehensive feature selection process was conducted, leading to the testing of five different algorithms for forecasting budget compliance. Finally, a secondary test was conducted, refining the features to include only those elements that procurement technicians can modify while also considering the two most accurate predictors identified in the previous test.

The findings indicate that employing the SMOTE method on the scraped data can achieve a balanced dataset. Furthermore, the results demonstrate that the Adam ANN algorithm outperformed others, boasting a precision rate of 68.1%.

The model can aid procurement technicians during the tendering phase by using historical data and analogous projects to predict performance.

Although the study reveals that ML algorithms cannot accurately predict budget compliance using procurement data, they can still provide project owners with insights into the most suitable criteria, aiding decision-making. Further research should assess the model’s impact and capacity within the procurement workflow.

Previous research predominantly focused on forecasting budgets by leveraging data from the private construction execution phase. While some investigations incorporated procurement data, this study distinguishes itself by using an imbalanced dataset and anticipating compliance rather than predicting budgetary figures. The model predicts budget compliance by analysing qualitative and quantitative characteristics of public project contracts. The research paper explores various model architectures and data treatment techniques to develop a model to assist the Client in tender definition.

In industrial buyer–supplier relationships, being an attractive customer has been found to result in superior supplier performance. However, there is a limited understanding of how these benefits transfer to the public domain. This study aims to explore the influence of customer attractiveness on supplier resource mobilization efforts toward the public sector.

A qualitative approach was used, focusing on in-depth interviews with 23 informants from 3 critical and complex supplier markets. The data were processed using inductive coding and thematic analysis.

The findings indicate that customer attractiveness in the public sector influences suppliers’ mobilization efforts on several dimensions. In addition to stimulating competition in the tender phase, customer attractiveness can yield important benefits to quality, supply stability and innovation during the business relationship. It appears imperative for the public sector to improve its standings with suppliers to both mitigate the apparent risk of sub-par treatment and to unlock the preferential supplier treatment associated with being an attractive customer.

Receiving increased mobilization from suppliers will result in better use of public money and help improve resilience and innovation in public procurement.

This study extends the research on customer attractiveness in the public sector by being the first to explore the range and nature of its influence on supplier mobilization efforts.

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.

In construction projects, underpayments can be recognised as one of the significant drawbacks that impact the success of a project. Research into underpayments is considered ambiguous and provides a limited reflection of the issue, which makes it complicated to trace how it originates in the first place. This study aims to examine the causes that lead to underpayments and develop a holistic synthesis of underpayments for subcontractors in the lifecycle of a construction project.

An open-ended and closed-ended questionnaire was used to collect the data using purposeful sampling with 28 construction stakeholders who ranged from main contractors, subcontractors and others (Small medium enterprises SMEs, Consultancies, Clients etc.). Data collected was analysed to trace drivers and the impact of underpayment and suggested mitigation strategies to be identified whilst viewing the perspectives of a main contractor and subcontractor.

The findings show that the most prominent driver for underpayments is variation disputes followed by cash flow. The research also suggests mitigation strategies such as collaborative working, more robust budget control and early identification of risks as potential remedies to overcome the underpayment issue. The research concludes with a framework that elicits the complexity underlying underpayments for subcontractors in construction projects.

The research evolves the understanding that underpayment is a complex phenomenon, relying heavily on the data/information exchange mechanism between the main contractor and subcontractors. This research provokes the need to understand underpayment further so it can be mitigated.

Public-private partnership (PPP) power projects are associated with varying risk factors. This paper aims to develop a fuzzy quantitative risk allocation model (QRAM) to guide decision-making on risk allocation in PPP power projects in Ghana.

A total of 67 risk factors and 9 risk allocation criteria were established from literature and ranked in a two-round Delphi survey using questionnaires. The fuzzy synthetic evaluation method was used in developing the risk allocation model.

The model’s output variable is the risk allocation proportions between the public body and private body based on their capability to manage the risk factors. Out of the 37 critical risk factors, the public sector was allocated 12 risk factors with proportions = 50%, while the private sector was allocated 25 risk factors with proportions = 50%.

To the best of the authors’ knowledge, this research presents the first attempt in Ghana at endeavouring to develop a QRAM for PPP power projects. There is confidence in the model to efficiently allocate risks emanating from PPP power projects.

This study explores the current status of risk management (RM) in Sri Lanka and the obstacles in implementing RM in Sri Lankan small construction projects.

The current research study adopted a quantitative research method. Using a purposeful sampling strategy, 100 construction companies engaged in small construction projects in Sri Lanka were selected and a questionnaire was distributed among top managerial employees of these companies. Employees belonging to 47 companies responded to the survey which provided information relating to 812 construction projects. The collected data were analyzed using the RM implementation index (RMII) and other quantitative measures such as mean, median and percentages.

The research findings indicated that RM incorporation was at a lower degree in small construction projects in Sri Lanka. The findings further indicated that RM incorporation was relatively high in the public construction projects compared to the private construction projects. The main obstacles identified through the survey for RM implementation were: “lack of funding”, “lack of time”, “low profit margin”, “not economical” and “lack of knowledge”.

The study was limited to exploring RM implementation in small construction projects in Sri Lanka. The study was limited to the building construction companies under the 150-million-rupee (approx. below 450,000 USD) financial limit registered with the construction industry development authority in Sri Lanka.

RM in small construction projects in developing countries is a relatively less explored domain. Sri Lankan construction industry is another relatively less explored domain in terms of new management technique implementation such as RM and value management. The quantitative approach used for the study revealed that RM implementation is at a lower degree in the small construction projects. Moreover, several obstacles pertaining to RM implementation were recognized through this study. These findings will be useful for the construction stakeholders to overcome the recognized barriers and effectively use RM in their respective construction projects.

The purpose of this paper is to evaluate the barriers militating against the adoption of robotics in the construction industry.

Robotics implementation barriers were obtained from the previous studies and then through questionnaire survey construction stakeholders in Nigeria evaluate these barriers. Consequently, these barriers were examined via the exploratory factor analysis (EFA) technique. Furthermore, a model of these barriers was implemented by means of a partial least square structural equation modeling (PLS-SEM).

The EFA results showed that these barriers could be categorized into two: cost and technology. Results obtained from the proposed model showed that platform tools were crucial tools for implementing cloud computing.

The novelty of this research work will be provided a solid foundation for critically assessing and appreciating the different barriers affecting the adoption of robotics.

Despite the quantity of collaborations, the vocational network of the housing production in Ankara during its first five years (1923–1928) remains dispersed. The aim of this study is to identify all the actors of housing production and their collaborations which shaped Ankara's urban development as the new capital city.

The study engages with the literature and archival documents to identify the actors of the housing production, i.e. architects, master-builders, public institutions, private companies, contractors and entrepreneurs, and their resultant vocational network in the housing production in Ankara during 1923–1928.

Due to different agendas, such as speculation, financial interests or patriotism, the construction industry in Ankara had become an arena where many paths intersected, forming an intertwined vocational network. The profession of contractor became popular, and local architects, engineers and even individuals of various other professions began to work as mediators for foreign companies and public institutions, which required support especially in large-scale projects.

The dispersed information revealed that the actors of the housing production remained mostly anonymous, or only the famous architects were commemorated; however, others could be found within the lines of the established literature on Ankara and/or in archival documents. This research not only focuses on “salient” actors but also highlights the “silent” actors of the housing production and prepares charts to clarify the vocational network in Ankara during its first five years to contribute to the future studies on Ankara and its housing.

This study identifies benefits and challenges of PL partnerships, and recommendations to improve the PL partnership process.

Qualitative data was collected via semi-structured interviews (n = 8) with Irish PL retail buyers (n = 4) and producers (n = 4). Data was coded and thematically analysed.

Three key themes were identified. Theme 1 provides an overview of the benefits of PL partnerships for producers (e.g. volume driven orders, increased efficiencies) and for retailers (e.g. unique products, meeting consumer demand). Theme 2 presents challenges of PL partnerships specific to small and large producers (e.g. small producers may need significant investment to upgrade facilities, while larger producers may require significant volume to justify adaptation of production lines). Challenges common to both (e.g. risks related to short-term contracts, concerns about brand identity) are also discussed. Theme 3 summarised recommendations for successful PL partnerships generally (e.g. setting clear expectations and goals, building rapport and trust), and recommendations specific to producers and buyers specifically (e.g. producers should diversify customers to reduce risk, and retailers should communicate needs and direction).

There is currently limited research on PL partnerships between producers and retailers. This study addresses this gap by identifying key aspects for producers to consider when entering PL partnerships and key aspects for retailers to be aware of to help improve the attractiveness and success of these partnerships.

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.