This research examines three data mining approaches employing cost management datasets from 391 Thai contractor companies to investigate the predictive modeling of construction project failure with nine parameters. Artificial neural networks, naive bayes, and decision trees with attribute selection are some of the algorithms that were explored. In comparison to artificial neural network’s (91.33%) and naive bays’ (70.01%) accuracy rates, the decision trees with attribute selection demonstrated greater classification efficiency, registering an accuracy of 98.14%. Finally, the nine parameters include: 1) planning according to the current situation; 2) the company’s cost management strategy; 3) control and coordination from employees at different levels of the organization to survive on the basis of various uncertainties; 4) the importance of labor management factors; 5) the general status of the company, which has a significant effect on the project success; 6) the cost of procurement of the field office location; 7) the operational constraints and long-term safe work procedures; 8) the implementation of the construction system system piece by piece, using prefabricated parts; 9) dealing with the COVID-19 crisis, which is crucial for preventing project failure. The results show how advanced data mining approaches can improve cost estimation and prevent project failure, as well as how computational methods can enhance sustainability in the building industry. Although the results are encouraging, they also highlight issues including data asymmetry and the potential for overfitting in the decision tree model, necessitating careful consideration.

Infrastructure investment has long been held as an accelerator or a driver of the economy. Internationally, the UK ranks poorly with the performance of infrastructure and ranks in the lower percentile for both infrastructure investment and GDP growth rate amongst comparative nations. Faced with the uncertainty of Brexit and the likely negative economic impact this will bring, infrastructure investment may be used to strengthen the UK economy. This study aims to examine how infrastructure funding impacts economic growth and how best the UK can maximize this potential by building on existing work.
The research method is based on interviews carried out with respondents involved in infrastructure operating across various sectors. The findings show that investment in infrastructure is vital in the UK as it stimulates economic growth through employment creation due to factor productivity. However, it is critical for investment to be directed to regional opportunity areas with the potential to unlock economic growth and maximize returns whilst stimulating further growth to benefit other regions. There is also a need for policy consistency and to review UK infrastructure policy to streamline the process and to reduce cost and time overrun, with Brexit likely to impact negatively on infrastructure investment.

Bamboo is one of the noble plant species in Ethiopia. Household (HH) income and construction role of highland bamboo (Oldeania alpina (K. Schum.) Stapleto) stands were assessed at Masha district, Southern Ethiopia. Three peasant associations (PAs), Yepo, Yina and Gada, 7–15 key informants and 68, 46, 31 households, respectively were interviewed about the cost and income of bamboo to compare with woody climbers, honey, and mushroom in 2021. Bamboo was one of the main sources of income in all PAs, at least for fencing or house construction. In Yepo, Yina and Gada bamboo accounts 0.7%, 28.1%, 16.3% of the HH NTFP income, respectively. The local people responded that bamboo constructed houses and fences were durable for 15–30 and 2–10 years, respectively. In constructing a 2.44–4.27 m radius local house in Yepo, Yina and Gada 2.4–6 m³, 4.1–5.82 m³ and 3.1–4.3 m³ bamboo culms were harvested at 15, 20, and 30 years interval, respectively by each HH. Bamboo young shoots were also seasonally used for food. Although bamboo provides multiple uses, like substitute for wood and environmental services, it was facing different problems of deforestation. Therefore, policy attention is highly important for bamboo sustainable utilization.

Weather is almost inevitable and plays an important role in determining the duration of construction projects. The construction industry ultimately thrives upon the physical input, put in by the labours. The majority of the construction projects are executed in the outdoor environment and hence face a high impact of weather conditions. This study therefore evaluated the influence of weather conditions on construction workers’ productivity in Jos, Plateau State and proceeded to make recommendations geared towards the improvement of construction workers’ productivity in Jos. The study was conducted through the direct observation method. Three hundred and ninety-six (396) works were purposively sampled in selected working sites. The outcome shows that during dry weather, there was considerably less significant productivity of manual excavation. In contrast, a large increase in blockwork and plasterwork productivity was observed with a percentage difference of 33%, 56.3% and 61%, respectively. On the other hand, during wet weather conditions, the labour productivity for manual excavation increases, whereas it decreases for block work and plasterwork with percentages difference of 58%, 40% and 47%, respectively. Besides, relative humidity and wind speed have no impact on labours’ productivity in dry and wet weather. Besides, the temperature has the most decisive impact on workers’ productivity. Moreover, wind speed and humidity have a lower influence on workers’ productivity. The construction industry stakeholder in Jos, Nigeria, would benefit from this study’s recommendations for reducing the influence of weather on the building sector. Besides, the output can be extended to other regions having similar characteristics.

The current era of Industry 4.0, driven by advanced technologies, holds immense potential for revolutionising various industries and fostering substantial economic growth. However, comprehending intricate processes of policy change poses difficulties, impeding necessary adaptations. Public apprehensions are growing about the inertia and efficacy of policy changes, given the influential role of policy environments in shaping development amidst resource constraints. To address these concerns, the study introduces the Kaleidoscope Model of policy change, serving as a roadmap for policymakers to enact effective changes. The study investigates the mediating impact of cultural change within the framework of the Kaleidoscope Model. The study delves into cultural influences by incorporating the Behavior Change Wheel (BCW) Theory. The methodology involves questionnaires survey, analysing using Structural Equation Modelling (SEM). The findings reveal that only the Policy Adoption and Policy Implementation components significantly affect the assessment of the effectiveness of the Construction 4.0 policy. Intriguingly, the final model demonstrates no discernible connection between the Kaleidoscope Model and the cultural influences. This study makes a noteworthy contribution to the realm of political science by furnishing a comprehensive framework and directives for the successful implementation of the Construction 4.0 policy.