Construction time prediction model for public building projects

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Shambel Kifle Alemu
Keyword(s):  
Regression Analysis ◽  
Addis Ababa ◽  
Linear Regression Analysis ◽  
Research Work ◽  
Time Cost ◽  
Construction Time ◽  
Time Model ◽  
Building Projects ◽  
Public Building ◽  
Content Type

PurposeThe aim of the study was to develop a practical construction time model for public building projects in Addis Ababa, Ethiopia.Design/methodology/approachThis research work used regression analysis and also exploratory scatter and residual plot techniques. Simple and multiple regressions were used for the investigation of the best fit time model. The analyses were carried out using IBM SPSS statistical software, version 20.FindingsThe result revealed that the Bromilow time-cost principle was moderately applicable. However, the cubic regression model (CUB) was found a better time-cost relationship. On the contrary, the study has shown a poor relationship between actual time and gross floor area. Furthermore, multiple linear regression analysis (MLR) consists of three statistically significant variables were found a better fit time model.Research limitations/implicationsThe study is limited to only six project scope factors. Further research is recommended to include more building projects of similar type and implications of other factors to improve the reliability of the models.Practical implicationsThe developed model was not intended as a replacement for detailed construction scheduling techniques. The resulting model is applicable for front-end predictions of construction duration.Originality/valueThe main parties involved in the building projects should apply the model for benchmarking a precise construction time during the early planning phase.

Factors affecting employee performance of PT.Kiyokuni Indonesia

2017 ◽  
Vol 59 (4) ◽  
pp. 602-614 ◽  
Author(s):  
Suharno Pawirosumarto ◽  
Purwanto Katijan Sarjana ◽  
Muzaffar Muchtar
Keyword(s):  
Leadership Style ◽  
Significant Influence ◽  
Employee Performance ◽  
Linear Regression Analysis ◽  
Research Work ◽  
Employee Motivation ◽  
Multiple Linear Regression Analysis ◽  
Primary Data ◽  
Content Type ◽  
Factors Affecting

PurposeThis study aims to examine, analyze and explain the influence of leadership style, motivation and discipline to employee performance simultaneously and partially at PT. Kiyokuni Indonesia. Design/methodology/approachThe primary data used in this study come from questionnaire on respondents’ motivation, discipline, leadership style and employee performance. From 451 people as the population, 82 respondents who met the criteria as a sample were chosen by using the Slovin formula. The analytical method used is multiple linear regression analysis using SPSS Version 22. FindingsThe results of this study indicate that there is a positive and significant influence simultaneously between leadership style, employee motivation and discipline on employee performance. The results also show that there is a positive and significant influence partially between leadership style, employee motivation and discipline on employee performance. Discipline is the variable of the most powerful influence on employee performance, so it needs special attention. Originality/valueThe respondents of this research work for a company which generates products through the work of hands (manual work) and aims to promote the products in the international market.

scholarly journals A review of causes of variation order in the construction of terrace housing projects in Malaysia

2019 ◽  
Vol 277 ◽  
pp. 03013
Author(s):  
Noraziah Mohammad ◽  
Zabidi Hamzah
Keyword(s):  
Construction Industry ◽  
Construction Projects ◽  
Construction Project ◽  
Extensive Literature ◽  
Time Cost ◽  
Construction Time ◽  
Building Projects ◽  
Housing Projects ◽  
Building Project

Variation order refers to any changes from the scope, plan, specification or contract document in the construction project. This changes of work is a common problem in construction projects in Malaysia. It is inevitable in any construction project and this problem can become more serious when variation order causes work progress to be impaired as a results it increased the construction time and cost that affects the construction industry in Malaysia. This paper critically review the causes of variation order in the construction industry on the double-storey terrace housing project in Malaysia. The discussions began with the construction industry in Malaysia and then related parties involved in the construction industry. The extensive local and abroad literature review on the definitions of variation order and analysis of past studies conducted on variation order and the previous study of the prediction model of variation. The extensive literature on variation order in the construction of building project may help to improve the performance in term of time, cost and quality of the construction of building projects in Malaysia.

Preoperative cross functional teams improve OR performance

2015 ◽  
Vol 29 (3) ◽  
pp. 343-352 ◽  
Author(s):  
Justin Bitter ◽  
Elizabeth van Veen-Berkx ◽  
Pierre van Amelsvoort ◽  
Hein Gooszen
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Performance Indicator ◽  
Medical Center ◽  
Linear Regression Analysis ◽  
Content Type ◽  
Surgical Department ◽  
Stepwise Reduction ◽  
And Performance ◽  
Functional Teams

Purpose – The purpose of this paper is to present the effect of the introduction of cross-functional team (CFT)-based organization, rather than, on planning and performance of OR teams. Design/methodology/approach – In total, two surgical departments of the Radboud University Nijmegen Medical Center (RUNMC) in the Netherlands were selected to illustrate the effect on performance. Data were available for a total of seven consecutive years from 2005 until 2012 and consisted of 4,046 OR days for surgical Department A and 1,154 OR days for surgical Department B on which, respectively 8,419 and 5,295 surgical cases were performed. The performance indicator “raw utilization” of the two surgical Departments was presented as box-and-whisker plots per year (2005-2011). The relationship between raw utilization (y) and years (x) was analyzed with linear regression analysis, to observe if performance changed over time. Findings – Based on the linear regression analysis, raw utilization of surgical Department A showed a statistically significant increase since 2006. The variation in raw utilization reduced from IQR 33 percent in 2005 to IQR 8 percent in 2011. Surgical Department B showed that raw utilization increased since 2005. The variation in raw utilization reduced from IQR 21 percent in 2005 to IQR 8 percent in 2011. Social implications – Hospitals need to improve their productivity and efficiency in response to higher societal demands and rapidly escalating costs. The RUNMC increased their OR performance significantly by introduction of CFT-based organization in the operative process and abandoning the so called functional silos. Originality/value – The stepwise reduction of variation – a decrease of IQR during the years – indicates an organizational learning effect. This study demonstrates that introducing CFTs improve OR performance by working together as a team.

Comparing usage between dynamic and static e-reference collections

2015 ◽  
Vol 34 (3) ◽  
pp. 78-88 ◽  
Author(s):  
Alain R Lamothe
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Linear Relationship ◽  
Reference Data ◽  
Linear Regression Analysis ◽  
Content Type ◽  
Dynamic Content ◽  
Reference Collection ◽  
Simple Count ◽  
Strong Linear Relationship

Purpose – The purpose of this article was to present the results of a quantitative analysis that compared usage levels between an e-reference collection that has experienced continual updated content and growth and an e-reference collection that has not experienced any recent changes. The aim of the study was to determine quantitatively if e-reference collections with dynamic content experience greater levels of usage compared to e-reference collections that are static in both size and content. Design/methodology/approach – E-reference data were separated into a dynamic collection and a static collection. Usage for e-reference belonging to the dynamic collection was compared to usage of e-reference belonging to the static collection. The number of e-reference was obtained by simple count. Additional statistics tracked include the number of viewings. A linear regression analysis was used to determine the strength of the linear relationship between collection size and usage. Findings – Results indicate that e-reference collections that continue to grow in both size and content also continue to experience year-to-year increases in usage. E-reference collections that remain static in size and content experienced a decline in usage. A linear regression analysis indicates the existence of an extremely strong linear relationship between dynamic content and usage. A weaker linear relationship was calculated for static content. Originality/value – To this author’s knowledge, this research is the first to systematically and quantitatively compare usage levels between e-reference titles from growing collections to collections that have not had any new titles added recently.

Socio-demographic influences on various consumer food safety indices: an empirical study of ethnic Goan pork sausage consumers

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Solomon Rajkumar ◽  
Renuka Nayar ◽  
Kavitha Rajagopal ◽  
Eaknath B. Chakurkar ◽  
Vismitha Shree Venkatesh ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Food Safety ◽  
Health Hazard ◽  
Linear Regression Analysis ◽  
Demographic Variables ◽  
Primary Data ◽  
Content Type ◽  
Pork Sausage ◽  
Cumulative Score ◽  
Safety Indices

PurposeThe purpose of this paper is to assess food safety knowledge, choice behavior and health hazard concerns of ethnic Goan pork sausage consumers through various consumer food safety indices and also to evaluate socio-demographic influences on various consumer food safety indices.Design/methodology/approachPrimary data in the form of 210 questionnaire responses were collected from Goan pork sausage consumers. Based on the responses, seven various consumer food safety indices were derived. The cumulative score of all the indices were normalized (0–1). The association between socio-demographic variables and consumer indices were evaluated using linear regression analysis, Pearson's correlation matrix, principal component analysis (PCA) and correspondence analysis (CA).FindingsThe results of the analysis indicate that the consumption of Goan pork sausages is most prevalent amongst younger people with high education having higher income. A majority of consumers have high score for the four consumer indices. The results of correlation analysis, regression analysis, PCA and CA revealed a significant association of consumer indices with socio-demographic variables.Originality/valueThe results of this study will provide a way forward for the evaluation of existing overall food safety concerns in the target population and in the future would be used for the promotion of good handling practices and health of Goan pork sausage consumers.

Wavelet and multiple linear regression analysis for identifying factors affecting particulate matter PM2.5 in Mumbai City, India

2019 ◽  
Vol 36 (10) ◽  
pp. 1750-1783 ◽  
Author(s):  
Vivekanand Venkataraman ◽  
Syed Usmanulla ◽  
Appaiah Sonnappa ◽  
Pratiksha Sadashiv ◽  
Suhaib Soofi Mohammed ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Control Measures ◽  
Data Set ◽  
Content Type ◽  
Factors Affecting ◽  
Significant Factors

Purpose The purpose of this paper is to identify significant factors of environmental variables and pollutants that have an effect on PM2.5 through wavelet and regression analysis. Design/methodology/approach In order to provide stable data set for regression analysis, multiresolution analysis using wavelets is conducted. For the sampled data, multicollinearity among the independent variables is removed by using principal component analysis and multiple linear regression analysis is conducted using PM2.5 as a dependent variable. Findings It is found that few pollutants such as NO2, NOx, SO2, benzene and environmental factors such as ambient temperature, solar radiation and wind direction affect PM2.5. The regression model developed has high R2 value of 91.9 percent, and the residues are stationary and not correlated indicating a sound model. Research limitations/implications The research provides a framework for extracting stationary data and other important features such as change points in mean and variance, using the sample data for regression analysis. The work needs to be extended across all areas in India and for various other stationary data sets there can be different factors affecting PM2.5. Practical implications Control measures such as control charts can be implemented for significant factors. Social implications Rules and regulations can be made more stringent on the factors. Originality/value The originality of this paper lies in the integration of wavelets with regression analysis for air pollution data.

Comparing usage between a Dynamic and a Static e-monograph Collection

2015 ◽  
Vol 34 (1) ◽  
pp. 17-26 ◽  
Author(s):  
Alain R Lamothe
Keyword(s):  
Regression Analysis ◽  
Quantitative Analysis ◽  
Linear Regression ◽  
Linear Relationship ◽  
Design Methodology ◽  
Linear Regression Analysis ◽  
Content Type ◽  
Dynamic Content ◽  
Simple Count ◽  
Strong Linear Relationship

Purpose – The purpose of this paper is to present the results from a quantitative analysis comparing usage levels between an e-monograph collection that has experienced continual growth and an e-monograph collection that has not experienced any recent growth whatsoever. The aim of the study was to determine quantitatively if e-monograph collections with dynamic content experience greater levels of usage compared to e-monograph collections that are static in both size and content. Design/methodology/approach – E-monograph data were separated into a Dynamic and a Static Collection. Usage for e-monographs belonging to the Dynamic Collection was compared to usage of e-monographs belonging to the Static Collection. The number of e-monographs was obtained by simple count. Additional statistics tracked include the number of viewings. A linear regression analysis was used to determine the strength of the linear relationship between collection size and usage. Findings – Results indicate that e-monograph collections that continue to grow in both size and content also continue to experience year-to-year increases in usage, whereas e-monograph collections that remain static in size and content experience a decline in usage. A linear regression analysis indicates the existence of a very strong linear relationship that exists between Dynamic Collection size and usage. A weaker linear relationship was calculated for Static Collection size and usage. Originality/value – This research is one of very few studies systematically and quantitatively comparing usage levels between e-monographs from growing collections to collections that have not had any new titles added recently.

Improving accuracy of conceptual cost estimation using MRA and ANFIS in Indonesian building projects

2018 ◽  
Vol 8 (4) ◽  
pp. 348-357 ◽  
Author(s):  
Dwifitra Jumas ◽  
Faizul Azli Mohd-Rahim ◽  
Nurshuhada Zainon ◽  
Wayudi P. Utama
Keyword(s):  
Regression Analysis ◽  
Cost Estimation ◽  
Fuzzy Inference ◽  
Early Stage ◽  
State Building ◽  
Building Projects ◽  
Inference System ◽  
Content Type ◽  
Proposed Model ◽  
West Sumatra

Purpose The purpose of this paper is to develop a conceptual cost estimation (CCE) model for building project by using a pragmatic approach, which is a mix of tools drawn from multiple regression analysis (MRA) and adaptive neuro-fuzzy inference system (ANFIS), to improve the accuracy of cost estimation at an early stage. Design/methodology/approach This paper presents a set of MRA and integrating MRA with ANFIS or MRANFIS. A simultaneous regression analysis was developed to determine the main cost factors from 12 variables as input variables in the ANFIS model. Cost data from 78 projects of state building in West Sumatra, Indonesia were used to indicate the advantages of the proposed model. Findings The result shows that the proposed model, MRANFIS, has successfully improved the mean absolute percent error (MAPE) by 2.8 percent from MRA of 10.7–7.9 percent for closeness of fit to the model data and by 3.1 percent from MRA of 9.8–6.7 percent for prediction performance to the new data. Research limitations/implications Because the significant variables are different for each building type, the model may be not appropriate for other buildings depending on the characteristics of building. The models can be used and analyzed based on the own historical project data for each case so that the model can be applied. Originality/value The study thus provides better accuracy of CCE at an early stage for state building projects in West Sumatra, Indonesia by using the integrated model of MRA and ANFIS.

Depression and association with diet diversity score among adolescent (14-19) students of Jimma town high school, Jimma, southwest Ethiopia

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mekonnen Tsehay ◽  
Shimelis Girma ◽  
Almaz Mamaru ◽  
Mubarek Abera
Keyword(s):  
High School ◽  
Regression Analysis ◽  
Dietary Diversity ◽  
Linear Regression Analysis ◽  
Severe Depression ◽  
Depression Symptoms ◽  
Depression Severity ◽  
Content Type ◽  
Diet Diversity ◽  
Dietary Diversity Score

Purpose Dietary patterns are important for the physical and psychological development of adolescents. The purpose of this study is to determine magnitude and severity of depression and its relation with diet diversity score (DDS) among adolescent high school students. Design/methodology/approach A cross-sectional study was conducted among 546 adolescents selected from schools using multistage sampling technique. Dietary intakes were assessed using a 24-h dietary recall, and depression severity and prevalence were assessed by PHQ-9A. A structured questionnaire was used to collect data. Linear regression analysis was used, and unstandardized beta (ß) coefficients with 95% confidence intervals (CI) were computed to determine the association of depression and its severity with dietary diversity score. Findings In all, 546 questionnaires were filled completely and consistently making a response rate of 97.3%. The dietary diversity score in 97 (17.8%) of the adolescents were between 1 and 3 (low dietary diversity score) but 259 (47.4%) scored greater than 6 (high dietary diversity score). Chi-square test revealed that with a decrease in DDS from highest to lowest level, the percentage of moderate to severe and severe depression slightly increased (3.4%). In addition, the percentage of moderate to severe and severe depression who consumed meat, fish and milk and dairy products slightly increased (3% and 3.2%). Multivariate adjusted regression analysis demonstrated that dietary diversity score was found to be inversely associated with depression severity and prevalence. Originality/value It was found that linear association between diet diversity and depression severity, and prevalence after adjustment for relevant con-founders. The study provided epidemiological evidence of a robust association of dietary pattern with depression symptoms' severity and prevalence in adolescents.

Can the correlation among Dow 30 stocks predict market declines?

2014 ◽  
Vol 40 (1) ◽  
pp. 33-50 ◽  
Author(s):  
Jeffrey S. Jones ◽  
Brian Kincaid
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Time Horizon ◽  
Design Methodology ◽  
Linear Regression Analysis ◽  
Trading Strategy ◽  
Content Type ◽  
Dow Jones Industrial Average ◽  
Portfolio Managers ◽  
The Relationship

Purpose – This paper aims to examine the relationship between the correlation among the 30 stocks in the Dow Jones Industrial Average and overall returns on the broader market from 1950 to 2008. Design/methodology/approach – The paper computes historical correlation of the 30 stocks in the Dow Jones Industrial Average and future returns on the S&P 500 index over various windows and examines the relationship between these two items using linear regression analysis. In addition, the paper develops a trading strategy based on the results. Findings – The paper finds that increased equity correlation serves as a leading indicator of overall market decline. Regression analysis shows that equity correlations are a statistically significant predictor of market decline, as measured by subsequent returns of the S&P 500 index. The significance of the results increases as the time horizon of the calculation is increased. With the exception of the 1990s, the findings are robust within decades. Originality/value – This is the first study that examines the relationship between the historical correlations among the Dow 30 stocks with future returns for the S&P 500 index. In addition, the paper develops an original trading strategy that achieves superior returns to a buy-and-hold strategy. The paper's findings are useful to portfolio managers, practitioners, and policymakers.

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