Paper Title Author/s and year of publication: (i.e. Author last name, 2021) Research question/s Research design/ methodology (survey, literature rev

Paper Title Author/s and year of publication: (i.e. Author last name, 2021) Research question/s Research design/ methodology (survey, literature review, mathematical model, etc) Main findings/results Suggestions for future research (if any)

Prediction based cost estimation technique in agile development Butt et al., 2023 What are the limitations of existing cost estimation techniques in agile development?

How can a predictions-based cost estimation technique address the challenges of frequent change requests in agile development?

What are the key components and categorizations used in the proposed cost estimation model?

What is the effectiveness of the proposed cost estimation technique in controlling cost and time increments in agile projects?

The research methodology includes a survey, interviews, and meetings with development teams to gather data on the challenges faced in agile software development. The study involves applying the proposed cost estimation technique to ongoing projects in software industries to assess its effectiveness. Statistical analysis is conducted to compare the proposed technique with existing estimation methods. Application of the SS Model to ongoing projects shows promising results in controlling cost and time increments due to change requests.

Statistical analysis of the SS Model demonstrates its effectiveness in improving cost estimation accuracy and project management in agile development.

Further validation of the SS Model in diverse agile development environments to assess its scalability and adaptability.

Longitudinal studies to evaluate the long-term impact of the SS Model on project outcomes and client satisfaction.

Comparative studies with other predictions-based cost estimation techniques to identify best practices and potential improvements.

Exploration of the SS Model's applicability to other industries or project management contexts beyond software development.

The Case-based Reasoning Model of Cost Estimation at the Preliminary Stage of a Construction Project. Zima, 2015 How can the Case-Based Reasoning (CBR) method be used to calculate the unit price of construction elements or works?

Can CBR be used to create a preliminary cost estimation model that reflects market prices?

Case-Based Reasoning (CBR):The primary methodology.

Data-driven approach:The model draws on a database compiled from real estimates taken from various construction project offer bids.

Similarity analysis and solution adaptation:The focus is on calculating unit prices based on finding similar cases in the database and modifying solutions for new situations.

CBR as a cost estimation method:The study suggests that CBR is potentially effective for calculating unit prices in construction by finding the most applicable examples from past bids.

Database of cost estimates:The creation of a database containing individual works/elements and associated costs from previous bids is key to the model.

Adaptability:The model incorporates automatic adjustments in cost estimations (based on location, inflation) and allows for user input when no similar existing cases are found.

Simplicity and Efficiency:These are emphasized as major advantages of the CBR model compared to traditional cost estimation approaches.

Enhancing the database:The abstract highlights the value of a large database for accurate calculations and the need to overcome regional and temporal discrepancies in pricing.

Further testing and validation:The authors suggest evaluating the model with a larger dataset against actual project costs to test and improve its performance.

Cost estimation and prediction in construction projects: a systematic review on machine learning techniques

Tayefeh Hashemi et al., 2020 What is the criteria for construction projects cost estimation.

How todetermine the criteria of construction projects based on application area, method applied, techniques implemented, journals, and the year of publication.

Review and Assess the existing models of machine learning techniques in cost estimation of construction projects. The research methodology used in this article is a systematic review. The authors looked at articles published from 1985 to 2020 in Google Scholar and Science Direct that used the keywords Construction, Cost estimation, Cost Prediction, Regression Analysis, Case Based Reasoning, Analogy, Artificial Intelligence Techniques. They included any articles that mentioned machine learning techniques in the title or abstract. After removing duplicates, they reviewed the remaining articles to see if they met their criteria. They then analyzed the data they collected based on the following: application area, method applied, techniques implemented, journals published in, and the year of publication. The paper discusses the findings of a systematic review on the use of machine learning techniques in construction project cost estimation. The authors identified 92 relevant articles published between 1985 and 2020. They found that a variety of machine learning techniques have been used in this domain, including artificial neural networks, case-based reasoning, and regression analysis. The authors also found that these techniques can be effective in improving the accuracy of cost estimates. The article suggests that deep-learning techniques have not been given enough attention in the field of cost estimation for construction projects. This systematic review suggests these techniques and models for future research and study.

Critical Risks to Construction Cost Estimation Ekung et al., 2021 To evaluate the sources, frequency, and significance of construction estimating risks.

Survey of quantity surveyors in Nigeria.

Seven sources of estimating risks were identified: estimating resources, construction knowledge, design information, economic conditions, expertise of the estimator, geographic factors, and cost data.

The top 3 critical risks had been low construction knowledge, incorrect cost information and changing government regulations. The authors suggest additional studies on the way these risks impact certain construction projects.

They also suggest that future research might establish a framework for lowering construction estimating risks.

Identification and assessment of risk factors affecting construction projects.

Abd El-Karim et al., 2017 The research question of this article is to identify and assess the factors that affect cost overrun and schedule overrun in construction projects. Research method: questionnaire survey. Through literature review and expert opinion, the researchers identified factors impacting cost and schedule overruns. They created a questionnaire to measure the impact for each factor. A questionnaire was sent to practitioners in the construction industry and data collection along with analysis using Crystal Ball software. The researchers developed probability distribution charts for each factor's likelihood, cost impact and schedule effect from the data. The impacts of cost overrun along with schedule overrun. The authors identify site conditions, resources, project parties and project features as potential sources of these issues. They also created a model of cost and time contingencies. The authors recommend future research concentrate on more sophisticated models of cost and schedule overrun prediction. Additionally they suggest that future research evaluates the performance of various risk mitigation methods.

References

Abd El-Karim, M. S. B. A., Mosa El Nawawy, O. A., & Abdel-Alim, A. M. (2017, August). Identification and assessment of risk factors affecting construction projects. HBRC Journal, 13(2), 202216. https://doi.org/10.1016/j.hbrcj.2015.05.001Butt, S. A., Ercan, T., Binsawad, M., Ariza-Colpas, P. P., Diaz-Martinez, J., Pieres-Espitia, G., De-La-Hoz-Franco, E., Melo, M. A. P., Ortega, R. M., & De-La-Hoz-Hernndez, J. D. (2023, January). Prediction based cost estimation technique in agile development. Advances in Engineering Software, 175, 103329. https://doi.org/10.1016/j.advengsoft.2022.103329

Samuel, E., Adeniran, L., Adu, E. (2021, January 1). Critical Risks to Construction Cost Estimation. Journal of Engineering, Project, and Production Management. https://doi.org/10.2478/jeppm-2021-0003Tayefeh Hashemi, S., Ebadati, O. M., & Kaur, H. (2020, September 15). Cost estimation and prediction in construction projects: a systematic review on machine learning techniques. SN Applied Sciences, 2(10). https://doi.org/10.1007/s42452-020-03497-1

Zima, K. (2015). The Case-based Reasoning Model of Cost Estimation at the Preliminary Stage of a Construction Project. Procedia Engineering, 122, 5764. https://doi.org/10.1016/j.proeng.2015.10.007