A Comprehensive Comparison of Air Pollution in Main Cities in Sri Lanka

Industrialization, increasing population and the vast usage of vehicles have been deterioratedthe quality of air in developing countries. Sri Lanka is one such developing country facing theproblem in quality of the air severely. Since Colombo is the commercial capital of Sri Lankait is a foremost victim of environmental pollution and many researches have been conductedto control the air pollution in Colombo. However when concerning the quality of air,attention should be paid on the other cities as well, which are more populated andindustrialized, since air pollution is a silent hazard that may even cause death to humanbeings. Main objectives of this research are to analyse the air quality data and to compare andcontrast the pollutant levels, at the four different locations Colombo, Kandy, Maharagamaand Kurunegala. Data were collected by a leading environment organization, Cleanco LankaLimited and published in “Ada” news paper. Concentrations measured in mg/m3 for the fivecriterion air pollutants; Carbon Monoxide (CO), Sulfur Dioxide (SO2), Nitrogen Dioxide(NO2), Ozone (O3) and Particulate Matter (PM 10) were gathered during the time period 1.00p.m. to 4.00 p.m. The period October 2010 to April 2013 was considered for this study. Dataare analysed using descriptive statistical techniques including summary measurements,graphical representations and correlation analysis. Furthermore, univariate statistical controlcharts are drawn to assess the quality of air of the selected cities. The data reveals that theconcentrations of CO and NO2 are high at Colombo and the concentrations of the fivepollutants are comparatively large at Maharagama on average, indicating that the other citiesmay also highly polluted as the commercial capital of Sri Lanka. However, the concentrationsof the air pollutants are decreasing after February, 2011 whilst the PM 10 concentrationshows erratic movements around the maximum permissible level of 0.5 mg/m3. It should beaffirmed that the CO concentration has not exceeded the maximum permissible level duringthe past two years. Moreover, the relationships between primary and secondary air pollutantssuch as O3 with CO and NO2 can be examined through the correlation structure of the data.

Usage of Knowledge Management Techniques in IT Based Company in Sri Lanka: A Case Study

AbstractKnowledge Management (KM) and Project Management (PM) are very substantial techniques to gain the competitive advantage within the Information Technology (IT) industry. In IT projects, it is essential to get the right knowledge to the right people at the right time. KM techniques are used to fulfill the above knowledge gaps. The main objective of this study is to determine the usage of KM techniques in an IT company in Sri Lanka. Simple random sample of size 108 is selected from the target population of all 150 project team members in the selected company. Since, the hypotheses were tested using statistical methods the positivism philosophy was used in this study. A deductive approach is used in cross-sectional time horizon and mixed approach is used to gather data. Collected data were analyzed to identify the usage of KM techniques in successful and failure projects. KM techniques were compared with respect to the status of the project (Success/Failure) and the category of the project (Government/Privet/Banking/Insurance/other). Male representation is higher than the female representation in the company. Majority of respondents belongs to the age group 26-30 and bachelor’s degree holders. More than half of the respondents do not have any KM qualification. Among the projects undertaken by the company 30% projects are related to insurance industry while government, banking, and private company with 20% each. The rest of the projects come under other category. Usages of the different type of KM techniques were examined. The successful projects mainly used after action review, brainstorming, collaborative virtual workshop, communication of practice, peer assist, learning review as important techniques while failure projects do not. In the successful projects knowledge banks is not considered as an important technique while in the failure projects does. The analyzed results stated that after action review, gone well note, learning review have significantly effect on all project categories. Moreover, blog, knowledge bases, storytelling and social networks are found to be effectiveness on successfulness of government and private projects.Keywords: Knowledge management, Project Management, Knowledge management technique

Factors Associated with Production Input Difference of a Manufacturing Plant in Sri Lanka: A Case Study

AbstractThe supply chain is a system of organizations, peoples, activities, information, and resources involved in moving a product or service from supplier to customer. As the whole supply chain is linked together, any inconsistency in one link can badly affect the overall supply chain. Each organization in the supply chain has its own internal individual supply chains. The internal supply chain is mainly based on the production demand and material supply to the production. Any inconsistency between the demand and the supply, directly affects the status of internal supply chain. Only few studies have been done on internal supply demand variance, and this study is one of the few approaches into this area. The main objective of this study is to identify the factors associated with production input difference of a manufacturing plant. This is an explanatory research, which is done using appropriate sampling methods and Vector Auto regressive (VAR) modeling. Eviews (7.0.0.1) version is used to analyze the data. First of all the data has been checked for stationary property and the related lag length has been selected. Then the VAR modeling techniques has been applied and later the diagnostic tests have been performed on the resulted models. In briefing the results, it is stated that style of the product (Style) does not impact the input variance models or downtime models. Considering input variance models, it is found that downtime at lag 1 does not have any impact on the input variance. Furthermore, the previous day input variance has a significant impact to the next day input variance. The style and previous day downtime influence the demand variance only in special cases. As heteroskedasticity is present in some of the models, exponential & power transformations have been done in order to avoid heteroskedasticity. But the results do not dramatically change due to transformations.Keywords: Factors, Internal Supply Chain, Manufacturing Plant, Vector Auto Regressiv