The Contribution of Workers’ Attributes on Sustainability of Construction Project Realization Goals—Survey on the Impact on Productivity in Croatia

Vidaković, Držislav; Hadzima-Nyarko, Marijana; Marenjak, Saša

doi:10.3390/su12239946

Cited by 7 publications

(4 citation statements)

References 65 publications

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“…Data mining uses a large number of data analysis technologies provided by the machine learning community and data management technologies provided by the database community. Machine learning is an important tool for data mining [16,17].…”

Section: Eoretical Basis Of Machine Learning and Data Miningmentioning

confidence: 99%

Construction Principles of Physical Fitness Training Objective System Based on Machine Learning and Data Mining

Wang

Sun

2022

Security and Communication Networks

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The objective is to address the issue of simplification of physical education classes offered by large colleges and universities. The evaluation standard of physical education curriculum is not unified. The physical education management system focuses on the functions of collecting information, sorting, and statistics and has low timeliness and guiding significance. This paper puts forward an analysis of the construction principle of physical fitness training target system based on machine learning and data mining. This paper uses informational analysis to statistically analyze the healthy behavior of college students, to guide the physical education of college students, and to propose a model for the analysis of healthy sports behavior of college students based on data mining technology. Create a decision tree template for students whose cardiovascular function does not meet the standard using the decision tree algorithm. The association rule algorithm is used to mine the association of five indexes of physical health, so as to judge the hidden law between students’ physical fitness and behavior habits and get the correlation information of various physical health indicators. The simulation results show that, through the prediction of college students’ healthy sports behavior data, when the sample point is 5, the original value data is 16, which is higher than the estimated value, the convergence of the overall data characteristic distribution is good, and the disturbance error is low. Therefore, using this method to analyze the application of college students’ healthy sports behavior has a high accuracy of sports-related data mining and can effectively guide college students’ sports management and training.

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Section: Eoretical Basis Of Machine Learning and Data Miningmentioning

confidence: 99%

Construction Principles of Physical Fitness Training Objective System Based on Machine Learning and Data Mining

Wang

Sun

2022

Security and Communication Networks

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“…The existing literature mainly focused on the measurement of labor productivity and the analysis of its influencing factors at the project level, such as project management model, worker skill, equipment [8], the implementation of building information modeling [9], and worker characteristics [10]. However, there is little literature on productivity at the industry level.…”

Section: Literature Reviewmentioning

confidence: 99%

How Can Information Technology Use Improve Construction Labor Productivity? An Empirical Analysis from China

Qin

Cui

et al. 2021

Sustainability

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Labor productivity is a significant indicator to measure the sustainable development potential and competitiveness of the construction industry. Under the background of the integration of global construction industry and information and communication technology (ICT), the pursuit of the growth of construction labor productivity (CLP) requires deepened understanding of how these technological advancements characterized by ICT take effect in the change of CLP as well as what the key factors are that led to the variation of CLP at this stage. The paper aims to investigate the effect of ICT progress on CLP and examine the key factors influencing CPL. Based on the data of 31 regions from the China Construction Industry Statistical Yearbook and the Local Statistical Yearbook during the period 2000–2018, this study proposed new methodology (Cobb–Douglas production function, growth rate model, and Malmquist Data Envelopment Analysis) for measuring the technology progress contribution and identified the key factors affecting the change of CLP. The analysis results illustrate that the information technology progress has a significant contribution to CLP growth, but the contribution rate is decreasing with the growing degree of development of the regional construction industry. Three main factors affecting the further improvement of CLP have been identified: human resources, research and development (R&D) investment, and ICT level. The findings can provide the decision-making reference and the general methodology for the local and international industry practitioners to improve the labor productivity performance of the construction sector.

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“…Motivation skill is the ability to inspire a person to achieve targeted goals. According to Vidaković et al (2020), motivation is a driver to an employee's productivity. For instance, the project team that is heedless of the sustainable project process is barely motivated (Hwang & Ng, 2013).…”

Section: Iv) Motivation Skillmentioning

confidence: 99%

The Improvement Factors of Leadership Skills among Project Managers in Pre-Construction Phase of Sustainable Construction Projects

Latiffi

Zulkiffli

2021

INTREST

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Leadership skills are required in any area, including the construction industry. Compared to conventional construction projects, the obstacles of practising leadership skills are more significant in sustainable construction projects. In the context of managing a project, a project manager is accountable for overseeing the project from the pre-construction phase to the post-construction phase. Nevertheless, project managers often encountered utmost difficulties in sustainable construction projects during the pre-construction phase. Despite that, improving leadership skills would emerge to boost project manager performance in managing sustainable construction projects. Thus, this paper aims to determine the improvement factors of leadership skills among project managers in the pre-construction phase of sustainable construction projects. A questionnaire survey was developed with 44 improvement factors of leadership skills among project managers in the pre-construction phase of sustainable construction projects, in which 153 experienced project managers in sustainable construction projects in Malaysia responded. Data were analysed using normality test, exploratory factor analysis (EFA) and reliability analysis via IBM SPSS version 24 software. The finding reveals that all improvement factors were significant to improve leadership skills among project managers in the pre-construction phase of sustainable construction projects. Hence, this paper's findings would assist project managers in grasping the improvement factors that can improve their leadership skills, particularly in sustainable construction projects.

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The Contribution of Workers’ Attributes on Sustainability of Construction Project Realization Goals—Survey on the Impact on Productivity in Croatia

Cited by 7 publications

References 65 publications

Construction Principles of Physical Fitness Training Objective System Based on Machine Learning and Data Mining

Construction Principles of Physical Fitness Training Objective System Based on Machine Learning and Data Mining

How Can Information Technology Use Improve Construction Labor Productivity? An Empirical Analysis from China

The Improvement Factors of Leadership Skills among Project Managers in Pre-Construction Phase of Sustainable Construction Projects

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