scholarly journals The application of cluster analysis to identify the occupational profile of people injured in accidents in the Polish construction industry

2018 ◽  
Vol 456 ◽  
pp. 012027 ◽  
Author(s):  
M Szóstak
Keyword(s):  
Cluster Analysis ◽  
Construction Industry ◽  
Occupational Profile

scholarly journals Classification of Polish voivodeships with regards to the accident rate in the construction industry

2018 ◽  
Vol 174 ◽  
pp. 04007 ◽  
Author(s):  
Tomasz Nowobilski ◽  
Irena Bagińska ◽  
Krzysztof Gawron
Keyword(s):  
Cluster Analysis ◽  
Construction Industry ◽  
Occupational Safety ◽  
Statistical Data ◽  
Occupational Accidents ◽  
Accident Rate ◽  
Central Statistical ◽  
Central Statistical Office ◽  
And Cluster Analysis

The article classifies Polish voivodeships into appropriate groups with a similar level of occupational safety in the construction industry. The basis for the adopted classification was statistical data published by the Central Statistical Office regarding population, employment in the construction industry, the value of construction production and the number of occupational accidents. The conducted research allowed a logical and correct, in terms of content, division of the Polish territory to be made, taking into account the aspect of occupational safety in the construction industry. Statistica software and cluster analysis were used to solve the problem.

Drivers for adopting reverse logistics in the construction industry: a qualitative study

2016 ◽  
Vol 23 (2) ◽  
pp. 134-157 ◽  
Author(s):  
Nicholas Chileshe ◽  
Raufdeen Rameezdeen ◽  
M. Reza Hosseini
Keyword(s):  
Cluster Analysis ◽  
Construction Industry ◽  
Reverse Logistics ◽  
Geographic Area ◽  
Structured Interviews ◽  
Content Type ◽  
Factors Affecting ◽  
Final Destination ◽  
Road Map ◽  
The Impact

Purpose – The purpose of this paper is to investigate and analyse the perceptions of South Australian construction practitioners on drivers affecting the implementation of reverse logistics (RL). In this context, RL is defined as the process of moving goods from their typical final destination for the purpose of capturing value or ensuring proper disposal. Design/methodology/approach – Semi-structured interviews were conducted with eight practitioners to collect data and the interview transcripts were analysed using the NVivo (version 10) package. Cluster analysis was used to cross-validate the findings and provide an in-depth insight into the findings. Findings – The findings indicate that most of the drivers identified in earlier research are relevant for the construction industry. In addition, the study identified some new drivers that are categorised as “targeted demands by an exclusive clientele”. These drivers were found to be complementary to the economic, environmental and social drivers as previously conceptualised. In addition, a set of factors affecting the strength of drivers that had been overlooked in previous studies emanated from the interview analysis. These include the type of project and the attributes of clients, both of which strongly affect the drivers of RL implementation in construction. Research limitations/implications – The major limitations are the relatively small size of the sample of interviewees and having interviewees from one geographic area with specific socio-economic characteristics. Practical implications – The identified drivers and the clustering of RL themes could be used by practitioners as a “road map” for the development of appropriate solutions to successfully promote RL within the construction industry. Organisational energies could thus be channelled towards the drivers that need the most improvement. Originality/value – The study contributes to this research sphere by employing cluster analysis to customise and contextualise the drivers that were previously identified. The study goes beyond the extant literature by discovering the prominent effects of these drivers on the impact of targeted demands by an exclusive clientele. This could be of great value in terms of creating avenues for future investigations on the topic.

scholarly journals Consideration of fire risks in construction on the basic of territories typology

2018 ◽  
Vol 251 ◽  
pp. 02016
Author(s):  
Vladimir Minaev ◽  
Boris Korobets ◽  
Tuan Dao ◽  
Phan Tuan Anh
Keyword(s):  
Cluster Analysis ◽  
Construction Industry ◽  
Fire Service ◽  
Optimal Management ◽  
Fire Services ◽  
Building Typology ◽  
Risks Assessment ◽  
Social Demographic ◽  
In Fire ◽  
Practical Recommendations

Subject of the study: The article considers assessments of fire risks in Vietnamese typological clusters. A set of factors characterized by economic, social, demographic, climatic indicators, as well as indicators that take into account processes of urbanization, electrification, trade and transport development, affecting both construction industry functioning and fire services activities in clusters are considered in building typology. Goal of the study: Triune and aimed at territories fire risks typology on the basic of cluster analysis – assessment of territorial differences in fire risks – justification models of optimal management of fire service resources in territorial clusters. Materials and methods: Methodological basis for fire risks assessment is the integral fire risks theory. Trends for each province in Vietnam from 2006 to 2016, and their averaged indicator for the same years are considered. Results: In term of fire risks, five homogeneous clusters of provinces are identified. Conclusions: Obtained typology in Vietnam makes it possible to develop practical recommendations for authorities, industries, including construction one, and fire service, on improving management of territorial resources taking into account fire risks, interaction between regional operational services, enhancing legal and regulatory support for insurance in construction industry.

Research on Shanghai Districts’ Construction Industry Competitiveness

2012 ◽  
Vol 174-177 ◽  
pp. 3397-3403
Author(s):  
Xiu Ming Li ◽  
Jian Guo Chen
Keyword(s):  
Neural Network ◽  
Cluster Analysis ◽  
Factor Analysis ◽  
Construction Industry ◽  
Macroeconomic Policies ◽  
Output Efficiency ◽  
Industry Competitiveness ◽  
Countermeasures And Suggestions ◽  
Pudong New Area

Shanghai districts’ construction industry competitiveness is evaluated and ranked, based on factor analysis, cluster analysis, neural network and the construction industry statistics of Shanghai statistics yearbook in 2007-2011. The evaluation shows that, there is imbalance in the 18 Shanghai districts’ industry scale and output efficiency competitiveness. And the industry in Pudong New Area is far more competitive than the rest of the various districts and counties, which just fits Chinese macroeconomic policies. New countermeasures and suggestions would be established in terms of the characteristics of each district which had been found.

scholarly journals The MATES Case Management Model: Presenting Problems and Referral Pathways for a Novel Peer-Led Approach to Addressing Suicide in the Construction Industry

2021 ◽  
Vol 18 (13) ◽  
pp. 6740
Author(s):  
Christopher M Doran ◽  
Lisa Wittenhagen ◽  
Edward Heffernan ◽  
Carla Meurk
Keyword(s):  
Mental Health ◽  
Case Management ◽  
Construction Industry ◽  
Intervention Program ◽  
Mental Health Problems ◽  
Work And Family ◽  
Management Model ◽  
Service Demand ◽  
Occupational Profile ◽  
Management Database

MATES in Construction (MATES) is a multimodal, peer-led, workplace suicide prevention and early intervention program developed to reduce the risk of suicide among construction industry workers through active facilitation of appropriate support. The MATES case management model provides an example of a nonclinical service for meeting the needs of individuals in the construction industry who, while at elevated risk of mental health problems and suicidality, are traditionally less likely to seek help. The aim of this research was to conduct an evaluation of the MATES case management database to quantify service demand, and to examine the demographic, occupational profile, presenting issues, referral pathways, and perceived benefit of case management among individuals who used this service. The research reports on routinely collected data from the Queensland MATES case management database, which contains records on 3759 individuals collected over the period 2010–2018, and findings from a small and opportunistic exit survey undertaken with 14 clients in 2019. Overall, findings suggest that the demand for case management through MATES has increased significantly and that clients felt that their needs and concerns were appropriately addressed. The most common presenting issues were relationship, work, and family problems, suicide, and mental health concerns. Findings confirm that causes of distress extend beyond the realm of mental disorder and span a range of psychosocial issues. Significantly, it offers an approach that may divert individuals in crisis away from presenting to over-run emergency departments, and towards services that are more equipped to meet their individual needs.

Organizational culture and total quality management practices in Indian construction industry

2019 ◽  
Vol 69 (5) ◽  
pp. 895-913 ◽  
Author(s):  
Vishal Singh Patyal ◽  
Sudhir Ambekar ◽  
Anand Prakash
Keyword(s):  
Cluster Analysis ◽  
Organizational Culture ◽  
Quality Management ◽  
Total Quality Management ◽  
Construction Industry ◽  
Management Practices ◽  
Successful Implementation ◽  
Total Quality ◽  
Content Type ◽  
Construction Organizations

Purpose The purpose of this paper is to establish the relationship between organizational culture (OC) and total quality management (TQM) practices in the Indian construction industry. Design/methodology/approach A questionnaire survey was conducted to draw valid empirical data from 200 construction firms in India. The dominant culture was identified using cluster analysis. Findings The findings of cluster analysis show four emergent clusters, namely, internal, flexible, comprehensive and control. The OC profile of the Indian construction organizations is dominated by internal focus characterized by the features of both group and hierarchical cultures of Competing Values Framework (CVF). Furthermore, the results revealed that the comprehensive focus culture is the most suitable culture in addition to the internal and flexibility focus cultures for the implementation of TQM in India. Practical implications Before implementing the TQM practices, managers in construction organizations need to be aware of cultural orientation emphasized in their organizations to facilitate the effective implementation of TQM. Originality/value This paper contributes to the existing literature by providing empirical evidence that leads to the association between OC and TQM practices. The study proposes besides the internal and flexibility focus cultures, the comprehensive focus culture within the Indian construction industry are key drivers for the successful implementation of TQM practices.

scholarly journals Cluster Analysis in Research of Accident Rate in Construction Sector

2018 ◽  
Vol 64 (3) ◽  
pp. 159-172
Author(s):  
W. Drozd
Keyword(s):  
Cluster Analysis ◽  
Construction Industry ◽  
Construction Site ◽  
Construction Sector ◽  
Critical Importance ◽  
Work Safety ◽  
Accident Rate

AbstractThe construction site and its elements create circumstances that are conducive to the formation of risks to work safety during the execution of works. Analysis indicates the critical importance of these factors in the set of characteristics that describe the causes of accidents in the construction industry. This paper attempts to analyse the characteristics of the construction site to indicate their importance in defining the circumstances of an accident at work. The research was carried out on the basis of data from the register kept by the District Labour Inspectorate in Krakow, Poland. Main substantive tasks include isolating patterns of accidents on site and identifying those of the analysed characteristics that are important in defining these patterns. In terms of methodology, the paper presents a method of analysing data resources by using means of conceptual grouping in the form of cluster analysis.

scholarly journals Klasyfikacja województw polski pod kątem wybranych wskaźników charakteryzujących budownictwo

2018 ◽  
Vol 27 (3) ◽  
pp. 310-318
Author(s):  
Bożena Hoła ◽  
Tomasz Nowobilski
Keyword(s):  
Cluster Analysis ◽  
Construction Industry ◽  
Occupational Accidents ◽  
Assembly Production

The article presents the methodology of classifying Polish voivodships with regards to selected indicators, such as the value of construction and assembly production, the number of people employed in the construction industry, the population of a given voivodship and the number of people injured in occupational accidents. Cluster analysis available in Statistica software was used to solve the problem.

Cluster analysis for large data sets: applications to individual aerosol particles from the mid-pacific

1992 ◽  
Vol 50 (2) ◽  
pp. 1488-1489
Author(s):  
Thomas W. Shattuck ◽  
James R. Anderson ◽  
Neil W. Tindale ◽  
Peter R. Buseck
Keyword(s):  
Cluster Analysis ◽  
Chemical Reactivity ◽  
Large Data ◽  
Large Data Sets ◽  
Particle Analysis ◽  
Data Sets ◽  
Halogen Chemistry ◽  
Complete Study ◽  
Components Analysis ◽  
Automated Scanning

Individual particle analysis involves the study of tens of thousands of particles using automated scanning electron microscopy and elemental analysis by energy-dispersive, x-ray emission spectroscopy (EDS). EDS produces large data sets that must be analyzed using multi-variate statistical techniques. A complete study uses cluster analysis, discriminant analysis, and factor or principal components analysis (PCA). The three techniques are used in the study of particles sampled during the FeLine cruise to the mid-Pacific ocean in the summer of 1990. The mid-Pacific aerosol provides information on long range particle transport, iron deposition, sea salt ageing, and halogen chemistry.Aerosol particle data sets suffer from a number of difficulties for pattern recognition using cluster analysis. There is a great disparity in the number of observations per cluster and the range of the variables in each cluster. The variables are not normally distributed, they are subject to considerable experimental error, and many values are zero, because of finite detection limits. Many of the clusters show considerable overlap, because of natural variability, agglomeration, and chemical reactivity.

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