scholarly journals Factors Influencing the Production of High Quality Aggregates for the Civil Construction Industry and the Essential Need for Crusher Automation

2000 ◽  
Author(s):  
Eric Trueman
Keyword(s):  
Construction Industry ◽  
High Quality ◽  
Factors Influencing

scholarly journals Factors Influencing Australian Construction Industry Apprentices’ Dietary Behaviors

2011 ◽  
Vol 6 (1) ◽  
pp. 59-66 ◽  
Author(s):  
Karin du Plessis
Keyword(s):  
Health Promotion ◽  
Construction Industry ◽  
Thematic Analysis ◽  
Food Choices ◽  
Dietary Behaviors ◽  
Blue Collar ◽  
Healthy Foods ◽  
Dietary Practices ◽  
Factors Influencing ◽  
Qualitative Focus Groups

To date there has been a theoretical and empirical gap in workplace-centered health promotion research—particularly as it applies to blue-collar men’s diets. To begin addressing the paucity of research, five qualitative focus groups ( N = 53) were conducted in Australian training colleges to explore the dietary behaviors of apprentices. Thematic analysis was used by the researcher who concludes that although some apprentices were health conscious and attempted to eat healthy foods, many had diets high in saturated fats and sugar. These types of diets are associated with increased risks for developing chronic disease and are associated with decreased life expectancy. As such it poses a serious challenge for health promoters. Apprentices’ dietary practices were also found to be moderated by convenience, availability, and cost of foods in their environment. Their nutritional beliefs, significant others, colleagues in the workplace, and their body image also influence their food choices.

Analysis Of Factors Influencing Acupuncture Clinical Effects: A Systematic Review

2021 ◽  
Author(s):  
Yali Liu ◽  
Honglin Jiang ◽  
Xiaotong Li ◽  
Xingyue Yang
Keyword(s):  
Systematic Review ◽  
Individual Difference ◽  
Current Status ◽  
Clinical Effects ◽  
High Quality ◽  
Psychological States ◽  
Factors Influencing ◽  
High Quality Evidence ◽  
Stimulus Parameters ◽  
Quality Evidence

Background: Acupuncture therapy has been widely applied all around the world. But there still lacks high-quality evidence to evaluate its clinical effects, safety and cost-effectiveness, which seriously restricts its further promotion and development. Acupuncture, as an operational intervention, is more complex than drug therapy. Factors involved in the acupuncture operation process, such as individual and interventional factors, may affect clinical effects. Purpose:s Through this systematic review, we attempt to analyze the current status of studies about the key factors influencing clinical effects, so as to provide evidence for the design of acupuncture studies. Methods: A literature research was conducted in six databases until May, 2020. Studies were screened and assessed by two authors independently. Data extraction was made after screening. We extracted the basic information of these studies, including publishing years and countries, population and factors influencing clinical effects.Results: Through the initial search in these six database, 6404 records were retrieved. After duplication and screening, a total of 355 studies were finally included in the qualitative analysis. About 88.5% of these studies were conducted in China with increasing number in the past decades, covering neurological disorders, orthopedic disorders, obstetrical and gynecological diseases, digestive diseases and so on; 239 studies focused on stimulus parameters which may influence effects, accounting for 67.3%, and 128, 44, 39, 32, 15, 11 studies discussed acupoints, patients’ pathological states, individual difference, psychological states, deqi, and other factors separately. Conclusion: There are more and more studies focusing on factors influencing acupuncture clinical effects, including stimulus parameters, acupoints, individual difference, patient pathological and psychological states. Based on this systematic review, several ignored factors should be considered for future researches, and more scientifically and objectively high quality evidence should also be proved.

A hybrid framework to model factors affecting construction labour productivity

2019 ◽  
Vol 24 (3) ◽  
pp. 630-654 ◽  
Author(s):  
Majid Parchami Jalal ◽  
Shahab Shoar
Keyword(s):  
Construction Industry ◽  
Labour Productivity ◽  
Content Type ◽  
Factors Affecting ◽  
Schedule Delay ◽  
Factors Influencing ◽  
Hybrid Framework ◽  
Novel Method ◽  
The Cost ◽  
The Impact

Purpose This paper aims to model different causal relations among factors interacting with labour productivity in order to recognize the most important factors influencing and influenced by it. Design/methodology/approach Top 60 factors affecting labour productivity were determined and grouped into 5 major groups by reviewing previous research and interviewing relevant experts. The interactions of factors were modelled using system dynamics (SD) approach. The resulting causal loop diagrams obtained from SD were then applied for identifying the most crucial factors influencing and influenced by labour productivity through the decision-making trial and evaluation laboratory (DEMATEL) method. The impact of factors on each other was finally determined based on the opinions of 63 experts selected from the Iranian construction industry. Findings The results indicated that factors such as fatigue, lack of labour motivation and lack of skill are the most influencing, and factors such as schedule delay and inflation in the cost of execution are the most influenced by labour productivity. In the end, a set of recommendations to improve construction labour productivity was also presented. Originality/value The main contribution of the study is proposing a novel method which is capable of providing insights into how causes and effects of construction labour productivity are interrelated. Furthermore, the proposed method makes this study distinct from previous research in the light of prioritizing factors and offering recommendations according to the interrelationships among factors.

Factors influencing fledgling production in little penguins (Eudyptula minor)

2004 ◽  
Vol 31 (3) ◽  
pp. 339 ◽  
Author(s):  
C. Knight ◽  
T. Rogers
Keyword(s):  
Breeding Season ◽  
Egg Laying ◽  
Breeding Biology ◽  
Single Variable ◽  
Nesting Habitat ◽  
High Quality ◽  
Factors Influencing ◽  
Little Penguin ◽  
Significant Model

An eight-year study was conducted on the breeding biology of the little penguin population at Lion Island. Forwards-selection Poisson regressions were used to determine whether variables such as year, date of lay, years since banding of each parent (indicator of age) and habitat influenced the fledgling numbers and average fledgling weight for adult pairs. 'Date of lay' provided the most significant model of fledgling numbers, while 'habitat' and 'year' as single-variable models also significantly influenced fledgling numbers. 'Date of lay' provided the most significant model of average fledgling weight. Future monitoring of the Lion Island colony therefore should focus on monitoring egg laying at the start of the breeding season, and maintaining high-quality nesting habitat.

scholarly journals Safety Climate Perceptions in the Construction Industry of Saudi Arabia: The Current Situation

2020 ◽  
Vol 17 (18) ◽  
pp. 6717 ◽  
Author(s):  
Ibrahim Mosly ◽  
Anas A. Makki
Keyword(s):  
Saudi Arabia ◽  
Construction Industry ◽  
Safety Climate ◽  
Health And Safety ◽  
Initial Step ◽  
Safety Education ◽  
Safety Behavior ◽  
Factors Influencing ◽  
Climate Perceptions ◽  
And Performance

Workers’ wellbeing and safety is important in the construction industry due to the high risk of accidents. Safety climate development is a positive initial step toward raising the safety levels of construction practitioners. This study aims at revealing the factors influencing safety climate perceptions in the construction industry of Saudi Arabia. A set of extracted factors from the literature was validated and used to design a comprehensive questionnaire survey. Data was collected from 401 personnel working on 3 large construction project sites in Saudi Arabia. Descriptive statistics and the crosstabulation algorithm, Kendall’s tau-b correlation test, were used to analyze the data. The study revealed a set of 13 factors influencing safety climate perceptions, which are: Supervision, guidance and inspection, appraisal of risks and hazards, social security and health insurance, workmate influences, management safety justice, management commitment to safety, education and training, communication, workers’ safety commitment, workers’ attitude toward health and safety, workers’ involvement, supportive environment, and competence. The results also indicate the significant and anticipated role of top management in safety climate at sites. Implications of this study include assisting construction industry stakeholders to better understand and enhance safety climate, which in turn will lead to improved safety behavior, culture, motivation, and performance.

scholarly journals Tension between Productivity and Respect for People in Construction

2020 ◽  
Vol 312 ◽  
pp. 05005
Author(s):  
Lesiba George Mollo ◽  
Fidelis Emuze ◽  
Nicholus Sishuba
Keyword(s):  
South Africa ◽  
Real Time ◽  
Construction Industry ◽  
Management System ◽  
Ethical Reasoning ◽  
Construction Site ◽  
Construction Sites ◽  
Factors Influencing ◽  
Major Factors ◽  
Structured Questionnaire

Productivity in the construction industry is declining in real-time. The decline in productivity is a source of worry for practitioners and researchers. The purpose of this paper is to ascertain major factors influencing productivity in relation to the notion of respects for people (RFP) in construction. The reviewed literature influences the semi-structured questionnaire used to survey construction professionals in Johannesburg, South Africa. The results reaffirm the tension productivity increment and the enhancement of RfP as both ideas appear to be moving in opposite directions on a typical construction site. It was discovered that respect for workers on a construction site is a major concern. The paper argues that ethical reasoning affects productivity. Therefore, an appropriate management system is required to improve the workers' perception of productivity and RfP working on construction sites.

scholarly journals Factors Influencing BIM Adoption for Construction Enterprises in China

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Ruixue Zhang ◽  
Yuyan Tang ◽  
Liang Wang ◽  
Zeyu Wang
Keyword(s):  
Construction Industry ◽  
Influencing Factors ◽  
Structural Equation ◽  
Equation Modeling ◽  
Key Factors ◽  
Process Data ◽  
Construction Enterprises ◽  
Factors Influencing ◽  
Hypothesis Model ◽  
Wide Range

The construction industry is one of the important pillars of the Chinese national economy. BIM, as a new information technology tool, provides an intelligent digital representation of buildings to support diverse activities and brings about a wide range of benefits throughout the life cycle of projects. However, BIM has not been widely adopted in construction enterprises in China. It is necessary to make a comprehensive and systematic analysis of the influencing factors for BIM adoption. This paper sums up 13 influencing factors from four aspects, namely, technology, economy, institution, and environment aspect. The questionnaire survey and statistical analysis were used to collect and process data which is applied to determine the influencing factors. Based on relevant literature, a hypothesis model was established by the structural equation modeling method. SPSS software and AMOS software were used to test the model. Then, the key factors influencing BIM adoption are induced. The results show that the key factors that influence BIM adoption in China include personnel quality, investment in personnel training, BIM standardization, and the influence of senior managers in the organization. Combined with the above conclusion, this paper puts forward some suggestions for promoting BIM adoption and specific measures to realize the wide application of BIM technology in the Chinese construction industry.

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