An estimation model of construction project segmentation for optimum project pricing

Shiue, Fang-Jye; Lee, Hsin-Yun; Zheng, Meng-Cong; Assefa, Sintayehu

doi:10.1108/ecam-08-2020-0596

Cited by 6 publications

(4 citation statements)

References 49 publications

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“…Žvelgiant iš užsakovo perspektyvos, vienas pagrindinių statybos rangos darbų viešųjų pirkimų tikslų -gauti optimalų rangovo kainos pasiūlymą pagal konkurencingą konkurso ekosistemą (Shiue et al, 2021). Statybos projekto vykdymo sėkmė priklauso nuo teisingų sprendimų, priimtų rengiant viešųjų pirkimų dokumentus.…”

Section: įVadasunclassified

Analysis of Public Procurement for Building Contracts

Vilkonis

2023

Science - Future of Lithuania

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Rapidly rising prices of construction materials and machinery in the construction market are also pushing up the cost of construction service. The main problem is that construction investment projects have been prepared and contracts between Contractors and Customers have been concluded at previous price and it is therefore necessary to look for opportunities to index the price of the construction contracts. The aim of the study is to analyse the procurement documents for construction contracts published on the Central Public Procurement Portal between 2019 and 2021. The analysis focuses on the pricing selection and price conversion options for public procurement documents for construction contract works. The economic and global geopolitical situation in the construction sector is reviewed. The critical situation in the construction sector due to the drastic increase in the cost of construction materials creates a risk that some contractors may not be able to complete their works in accordance with the signed construction contract. The essence of the article is to propose to the contracting authorities, following an analysis of the procurement documents for construction contracts, solutions to the problem by adding conditions to the procurement documents which will help to minimise the possibility of disputes between the contractors and the client.

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Section: įVadasunclassified

Analysis of Public Procurement for Building Contracts

Vilkonis

2023

Science - Future of Lithuania

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“…The project needs to be subdivided into more detailed work steps at each stage, and one or more project management tools must be used at each stage [10]. Project tools are many, such as project management maturity models (PMMMs) [23], critical path method (CPM), process evaluation and review techniques(PERT) [24], critical chain project management (CCPM) [25] and increasingly popular hybrid methods [26].…”

Section: Project Overviewmentioning

confidence: 99%

Fuzzy Assessment of Management Consulting Projects: Model Validation and Case Studies

Sun,

Ni,

Huang

2023

Mathematics

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Management consulting (MC) has been heavily involved in emerging business opportunities in mainland China. However, there are no well-known local MC project management models to help evaluate whether an MC project can be successful or not. This paper reports a model for the self-assessment of management consulting projects, which has been validated by 15 experts and 13 cases. The new model, with seven factors that are critical to the success of MC projects, was developed from a literature review. The model was then verified by developing a questionnaire that was sent to 15 experts and using Dempster–Shafer theory to obtain the weight of each part of the model. The model was applied to 13 real cases to verify its effectiveness in evaluating an MC project. This new MC model can help consulting teams to conduct assessments in the early and middle stages, and evaluate in the late stage, of consulting projects, and also can help teams improve the probability of project success and client satisfaction. It can be used by consultants, client companies, or both.

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“…For large projects, project segmentation and planning the size of contract packages in construction bids is a complex and critical issue. Shiue et al. (2020) aim to develop an integrated model for planning project segmentation.…”

Section: Literature Reviewmentioning

confidence: 99%

“…For large projects, project segmentation and planning the size of contract packages in construction bids is a complex and critical issue. Shiue et al (2020) aim to develop an integrated model for planning project segmentation. Biruk et al (2017) developed a parametric approach, which was a combination of the Analytic Hierarchy Process (AHP) and linear programming model for the purpose of making a decision about whether to bid or not based on a calculation of the total price of the bid.…”

Section: Chaid and Crt Decision Tree Algorithmsmentioning

confidence: 99%

Employment of CHAID and CRT decision tree algorithms to develop bid/no-bid decision-making models for contractors

Gündüz

Al-Ajji

2021

ECAM

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Purpose Bid/no-bid decision is a significant and strategic decision, which must be finalized at an early stage of the bidding process. Such decision-making may have significant impact on the performance of the contractors. Using Chi-square Automatic Interaction Detector (CHAID) and Classification and Regression (CRT) decision tree algorithms, this paper aims to develop bid/no-bid models for design-bid-build projects for contractors. Design/methodology/approach The models in this study have been developed using CHAID and CRT algorithms. Thirty-four bid/no-bid key factors were collected via extensive research. The bid/no-bid factors were listed based on their importance index as a result of a questionnaire distributed among the construction professionals. These factors were divided into five main risk categories – owner, project, bidding situation, contract and contractor – which were taken as inputs for the models. Split-sample validation was applied for testing and measuring the accuracy of the CHAID and CRT models. Moreover, Spearman's rank correlation and Analysis of Variance (ANOVA) tests were employed to identify the statistical features of the received 169 responses. Findings The key bid/no-bid factors in construction industry were categorized in five related groups and ranked based on the relative importance index. It was found that the top 6 ranked bid/no-bid factors were (1) current workload, (2) need for work, (3) previous experience with employer; (4) timely payment by the employer; (5) availability of other projects for bidding (6) reputation of employer in the industry. Matrix comparison between all bid/no-bid groups was performed using Spearman's correlation to measure the relationship between each of the two paired groups. It was concluded that all the relationships were positive. Originality/value Existing bidding models require many inputs and advanced understanding of mathematics and software to run the model. Contractors tend to use easy, fast and available support methods. Excluding a great number of the bid/no-bid factors may affect the final decision. This paper proposes a bid/no-bid decision tree models for contractors of different sizes. It is the first study in the literature, to the best of authors' knowledge, to study bid/no-bid decision with the proposed decision tree algorithm. The proposed models in this study overcome the shortfalls of most previous models such as avoiding the complexity and difficulties of applying the concept. The proposed model will provide the contractors with a bid/no-bid decision based on the input for the defined bid factor groups. The proposed models display the soft spots and hot spots between the independent and dependent variables, which leads to a better decision. The proposed models display the result effectively in visual terms, easy to understand and easy to apply. The proposed models are a form of multiple effect (or variable) analysis which allows the companies to explain, describe, predict or classify an outcome.

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An estimation model of construction project segmentation for optimum project pricing

Cited by 6 publications

References 49 publications

Analysis of Public Procurement for Building Contracts

Analysis of Public Procurement for Building Contracts

Fuzzy Assessment of Management Consulting Projects: Model Validation and Case Studies

Employment of CHAID and CRT decision tree algorithms to develop bid/no-bid decision-making models for contractors

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