Difference between revisions of "ANLY482 AY2017-18T2 Group18"
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| + | <p style="text-align:center; font-weight: bold; font-size: 28px;">Using Multiple Linear Regression to Analyse Factors Affecting Costs Incurred for Cleaning Projects: A Case Study of a Cleaning and Conservancy Company in Singapore</p> | ||
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<div style="border-style: solid; border-width:0; background: #0000CD; padding: 7px; font-weight: bold; text-align:left; line-height: wrap_content; text-indent: 20px; font-size:20px; font-family:Century Gothic;border-bottom:5px solid white; border-top:5px solid black"><font color= #FFFFF>Project Introduction</font></div> | <div style="border-style: solid; border-width:0; background: #0000CD; padding: 7px; font-weight: bold; text-align:left; line-height: wrap_content; text-indent: 20px; font-size:20px; font-family:Century Gothic;border-bottom:5px solid white; border-top:5px solid black"><font color= #FFFFF>Project Introduction</font></div> | ||
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| + | LS 2 Services Pte Ltd is a local cleaning and conservancy company that provides building cleaning services, landscape care and maintenance services activities in Singapore. For each prospective project site, costs incurred is estimated before tender is submitted. Expected costs incurred for each project has always been estimated based on the experience and professional judgement of its top management. However, such a method is not sufficient in cost-estimation as seen from several instances of loss-making projects. In this paper, we use multiple linear regression to build an explanatory model to find out what affects the various cost components incurred for conservancy project types. | ||
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| + | Explanatory variables such as dwelling units and commercial units converted to Equivalent Dwelling Units (EDU) are derived from identifying the facility descriptions of various project sites. The model being built for each cost component will help identify key possible cost drivers, as well as analyse whether an increase in any of the explanatory variables determined has an impact on manpower headcount as a cost driver. | ||
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Latest revision as of 21:18, 13 April 2018
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Using Multiple Linear Regression to Analyse Factors Affecting Costs Incurred for Cleaning Projects: A Case Study of a Cleaning and Conservancy Company in Singapore
LS 2 Services Pte Ltd is a local cleaning and conservancy company that provides building cleaning services, landscape care and maintenance services activities in Singapore. For each prospective project site, costs incurred is estimated before tender is submitted. Expected costs incurred for each project has always been estimated based on the experience and professional judgement of its top management. However, such a method is not sufficient in cost-estimation as seen from several instances of loss-making projects. In this paper, we use multiple linear regression to build an explanatory model to find out what affects the various cost components incurred for conservancy project types.
Explanatory variables such as dwelling units and commercial units converted to Equivalent Dwelling Units (EDU) are derived from identifying the facility descriptions of various project sites. The model being built for each cost component will help identify key possible cost drivers, as well as analyse whether an increase in any of the explanatory variables determined has an impact on manpower headcount as a cost driver.
