ABSTRACTThe its own definition of what is considered

ABSTRACTThe project will be on a statistical analysis of Small Medium-sized Enterprises (SMEs) in Brunei Darussalam. The sole purpose of the project is designed to extract data and techniques used in the derivation of the statistical analysis. This project will be handled by:Muhammad Arif Bin Junuin (14B3145)Siti Fatima binti Mahdan (14B3298)Syarfa’ Syazana binti Hj Mohd Hamzani (14B3323)The researchers will analyse the performance of SMEs by developing a structural model based on the data collections which obtained through Department of Economic Planning and Development (JPKE) or/and Darussalam Enterprises (DARE). TABLE OF CONTENTi Abstract1 Introduction2 Objectives3 Methodology3.1 Study Design3.2 Data Collection3.3 Variables3.4 Procedure3.4.1 Logistic Regression3.4.2 Longitudinal Analysis4 People Involved5 Potential Outcome of Research6 Schedule7 Ethical Considerations8 References1 INTRODUCTION              The project is conducted for a statistical analysis of Small Medium-size Enterprises (SMEs) in Brunei Darussalam. There is consensus among policy makers, economists and business experts that SMEs are drivers of economic growth. A healthy SMEs sector contributes prominently to the economy through creating more employment opportunities, generating higher production volumes, increasing exports and introducing innovation and entrepreneurship skills. SMEs are business that maintain revenues, assets or a number of employees below a certain threshold. Every country and economic organization has its own definition of what is considered a small and medium- sized enterprises. SMEs are non subsidiary, independent firms which have been identified as important role in industrial development that have high potential in contributing to the diversification of the economy. In Brunei Darussalam, SME is defined as business establishments having 100 employees or less. Micro enterprises is defined as a business that has fewer than 6 employees, small enterprises from 6 to 50 employees and whereas, medium enterprises 51 to 100 employees. (Kadai, 2012)  2 OBJECTIVESA particular focus is directed to estimate and ascertain the size and the state of the Brunei Darussalam SMEs sector and economic performance is assessed based on contribution of SMEs by size and sector value add and employment in Brunei Darussalam economy. This study is designed to research key areas of business performance including profitability as well as business confidence and satisfaction in the support of Brunei government. From the findings of the report, the researchers will formulate appropriate strategies and initiatives over the coming years to improve the SMEs sector as a whole and hopefully, increase their value add to the Brunei Darussalam economy, in consistent with the growth of Brunei Darussalam economy. The following questions were asked to guide the discussion: How do we define and categorize businesses.What are the odds of a start-up businesses to succeed?How do different variables affect the ease of business?The type of business most likely to thrive in Brunei.How long do SMEs typically survive?Do SMEs contribute to overall Brunei economy?Do SMEs contribute to employment rate?Percentage of contribution of small businesses to Brunei exports?What is the contribution of small businesses to Brunei’s gross domestic product (GDP)?3 METHODOLOGY 3.1 STUDY DESIGNThe researchers will illustrate the study case between 2010 and 2016 in terms of revenue, employment growth, economic growth, productivity of SMEs sector in Brunei. 3.2 DATA COLLECTIONThe data collection for the study case will be obtain and extract from Department of Economic Planning and Development or/and Darussalam Enterprises. Statistical techniques may introduce an element of subjectivity into interpretation and analysis of the data. The data that researchers looking forward are:The number of SMEs in BruneiThe number of employee that work for SMEsThe number of jobs created by small businessesThe number of SMEs that still surviveThe age, experience and education levels background of SMEs ownerThe contribution of small business to Brunei’s gross domestic product (GDP)The contribution of small businesses to Brunei exportsThe number of SMEs appear and disappear each year3.3 VARIABLESCategorical group variables may be used to calculate the statistical analysis. The variables are:Employee:Number (or percentage) of local employee and foreign employee working in SMEs.Employment rate:SMEs share in employment rate.Sales revenue:Income from sales of goods and services, minus the associated cost.Goods and/or services classification:e.g. Food and Beverages, Clothing, Travel and etc.Location of business:Commercial or non-commercial area.Continuous variables may be used to calculate the statistical analysis. The variables are:Length of business operation:Number of years of operation since establishment3.4 PROCEDURE3.4.1 LOGISTIC REGRESSIONThe statistical method and techniques that researchers will be using to study the data are Logistic Regression. Logistic Regression is a classification procedure best represented by the likelihood of an outcome as the core concept, which are sometimes better scale than probability to represent chances. The likelihood of an outcome is derived from a logit function on the dependent variable, where the variables represents a probability of success or failure.By using a Logistic Regression, statistical researchers could determine whether the SMEs in this case study become more successful or otherwise in terms of variables such that revenue, employee and business type. The following is the proposed logistic regression model for finding the odds of success of SMEs:Odds of success = ?0 + ?1(Revenue) + ?2(Employee) + ?3(Goods and Service Classification) + ?4(Business location) + ?5(Length of Business Operation)3.4.2 LONGITUDINAL ANALYSIS Longitudinal Analysis which is the study of short series of observations obtained from many respondents over time and is also referred to as panel analysis of a cross-section of time series, or repeated measures, or growth curve analysis (polynomials in time), or multilevel analysis where one level is a sequence of observations from respondents.By using this method, the researchers can analyse performance of Brunei Economy against SMEs in yearly basis. Longitudinal Analysis will also assist in finding survival rate of SMEs.4 PEOPLE INVOLVEDIn the course of this project, the parties involved will be:The researchersDepartment of Economic Planning and/or Development (JPKE) and Darussalam Enterprise (DARe):Data will be obtained from either JPKE or DARe and ethics approval will be neededSMEs in Brunei:Details of SMEs will be used from data obtained5 POTENTIAL OUTCOME OF RESEARCHIn Brunei Darussalam with limited resources, the accelerated way to enhance economic growth is to  innovate SMEs. SMEs benefited economy of Brunei Darussalam through creating employment and provide encouragement to economic stability. Labour productivity increases as SMEs in Brunei increases. It is prevalent in nationwide, employees in SMEs tend to receive lower wage level than large companies as more innovative companies employ highly educated employees.6 SCHEDULESchedule Plan Dates and Duration (tentative)Project Report Proposal31st January 2018Data Collection1st February 2018     –    14th February 2018 Analyses15th February 2018   –    28th February 2018Write Up a Report1st March 2018         –    21st March 2018Preparing slides for presentation22nd March 2018      –    31st March 2018Practicing presentations2nd April 2018Final Report & Presentation 18th April 20187 ETHICAL CONSIDERATIONSThis project may require ethics approval as the researchers need several data of SMEs informations to analyse the SMEs performance as it involved “SMEs confidential information” from the SMEs sectors, as for example; Income, Number of employees and contribution to Gross Domestic Product (GDP). Thus, these activities will be conducted professionally and ethically. The researchers will ensures that all the data information will be kept confidential as the activity needs to respect SMEs privacy and confidentiality.


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