Papers by THARAKA N . PERERA
Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems
Attitudes are the mental dispositions people have towards others and the current circumstances be... more Attitudes are the mental dispositions people have towards others and the current circumstances before making decisions that result in behavior Attitudes influence an individual’s choice of action, and responses to challenges, incentives and rewards. Football is a world popular sport which needs more physical and mental fitness. Football even in those instances it truly is mind over body. Now a days in Sri Lankan sport field the female participation for the football matches have developed. So the main objective of this study is to comparison of attitudes towards the competition of female football players in National and Junior National level in Sri Lanka while the specific objectives are to evaluate the attitude of football players’ entirety of the force, meaning for the competition, assessment of strength of the opponents, guidance for the opinions of others, in National level female football players and o evaluate the attitude of football players’ entirety of the force, meaning for...
EPRA International Journal of Multidisciplinary Research (IJMR), 2020
Attitudes are the mental dispositions people have towards others and the current circumstances be... more Attitudes are the mental dispositions people have towards others and the current circumstances before making decisions that result in behavior Attitudes influence an individual's choice of action, and responses to challenges, incentives and rewards. Football is a world popular sport which needs more physical and mental fitness. Football even in those instances it truly is mind over body. Now a days in Sri Lankan sport field the female participation for the football matches have developed. So the main objective of this study is to comparison of attitudes towards the competition of female football players in National and Junior National level in Sri Lanka while the specific objectives are to evaluate the attitude of football players' entirety of the force, meaning for the competition, assessment of strength of the opponents, guidance for the opinions of others, in National level female football players and o evaluate the attitude of football players' entirety of the force,...
EPRA International Journal of Multidisciplinary Research (IJMR), 2020
Attitudes are the mental dispositions people have towards others and the current circumstances be... more Attitudes are the mental dispositions people have towards others and the current circumstances before making decisions that result in behavior Attitudes influence an individual's choice of action, and responses to challenges, incentives and rewards. Football is a world popular sport which needs more physical and mental fitness. Football even in those instances it truly is mind over body. Now a days in Sri Lankan sport field the female participation for the football matches have developed. So the main objective of this study is to comparison of attitudes towards the competition of female football players in National and Junior National level in Sri Lanka while the specific objectives are to evaluate the attitude of football players' entirety of the force, meaning for the competition, assessment of strength of the opponents, guidance for the opinions of others, in National level female football players and o evaluate the attitude of football players' entirety of the force,...
NRCASS Full, 2018
Financial literacy has direct impact on financial decision making. In present society there are s... more Financial literacy has direct impact on financial decision making. In present society there are some troubles with lack of financial literacy. According to the previous literature in many countries, one can identify various factors are affecting to financial literacy rate. Main objective of this study is identifying the age group which is highly financial literate in Sri Lankan context. As well as identifying the other factors affected to financial literacy rate. This study was selected 300 households using simple random sampling technique as the sample from 1442 number of households in the Wewala West GN division which is the population of this study. Here only used primary data for research purposes and they were collected through structured questionnaire. For the analysis purposes analytical tools that validity analysis, frequency analysis, factor analysis, weighted average, chi square test and also one way ANOVA have used for analysis part of this study. This study find that gender, household's monthly income, education level, sector of job and age category are significantly affecting factor for the financial literacy rate while race is not significantly affect to financial literacy rate. Education level and age are the most important factors among the affected factors. And also this study finds that there is a different between age groups on financial literacy rate and people between age 36-50 and also above 60 groups are significantly have high level of financial literacy rate.
IPRC Full, 2018
In present society several severe troubles which arise due to the lack of financial literacy and ... more In present society several severe troubles which arise due to the lack of financial literacy and specially issues regarding retirement life confidence are observed. A very few out of the Sri Lankan population have retirement plans while a majority have a blank idea about it. Several factors can be identified which determine this difference of numbers. According to the previous studies in many countries, financial literacy rate is a considerable factor among other factors which decide whether an individual has a retirement plan or not. Research problem of this study is to check whether financial literacy rate is a significant factor which determines owning a retirement plan in the Sri Lankan context. In addition, specific objectives of this study are constructing indices for financial literacy and retirement life confidence, identifying the basic demographic factors affecting the financial literacy and retirement life confidence. A sample of 300 households from Wewala West GN division of Colombo District is selected for this research using simple random sampling technique. Structured questionnaire was used to gather data which contained basically 3 parts. Indices for financial literacy rate and retirement life confidence are constructed using weighted average method. With the use of these index values, people are categorized into two categories as high and low using the median value of each index. It was identified some factors including education level and age have a significant impact on the financial literacy rate but the race does not have a significantly effect. As well as there are some factors including monthly income, education level and ownership of the house which are significantly effect to retirement life confidence while gender, marital status, race, number of dependents and sector of job does not have a significant effect on retirement life confidence. Finally, it can be concluded that if someone has good financial literacy rate, such respondents tend to choose a retirement plan. Thus there is a relationship between financial literacy rate and having a retirement planning.
DemARS, 2019
Introduction
Aging population, which results from rapid demographic transition, is a key global d... more Introduction
Aging population, which results from rapid demographic transition, is a key global demographic challenge which will continue as an issue in both developed and developing nations during the twenty-first century (Niessen & Gibsen, 2000; Ettinger, 1997). Sri Lanka is the first country which reached demographic transition among the South Asian countries and Sri Lanka reports the highest aging population among South Asian countries as percentage (Menike, 2014). Therefore, Sri Lanka is rapidly experiencing aging problem. As a developing country Sri Lanka has faced socio-economic issues and challenges related to population ageing and aging population is burden to the government (Perera, 2017). As a result of increasing load of aging population, there is rapid increasing the number of enrolment to elders’ home (Luo, Xue & Zhang, 2018). If the study can identify the factors influencing aging populations’ intention to enroll in elders’ homes, it would be significant for get decisions on aging populations’ well-being.
Research Objectives
1. Identify the demographic factors influencing the intention of aging population in enrolling to elders’ homes.
2. Identify the social factors influencing the intention of aging population in enrolling to elders’ home.
Methodology
A sample of 40 elders from two elders’ home in Kesbewa AGA division is selected for this sample survey (2019) using convenience sampling technique. Researcher used convenience sampling technique to select the sample for this study and sample size limit to 40 elders. Structured interview technique is used to gather primary data and secondary data from previous literature is also used to identify trends of aging population’s intention to enroll in elders’ homes. Gender, marital status,
race, religion, monthly family income, number of family members, occupation and level of education are consider as demographic factors. On the other hand avoiding suffer and worries, no one care after them, economic difficulties and avoidance of children are consider as social factors. Analysis purposes frequency analysis used to identify the social factors and one sample chi square test as non-parametric statistics used to identify the significant demographic factors. Researcher build hypotheses as the categories of each demographic factor occur with equal probabilities. If the null hypothesis reject, it can conclude that demographic factor is significantly influencing the intention of aging population in enrolling to elders’ home.
Results and discussion
It is better to get idea on demographic characteristics of the sample, before it identify the demographic factors influencing the intention of aging population in enrolling to elders’ homes.
Samaja Vimarshana, 2019
In last two years according to the statistics extracted from periodic reports of Commercial Bank ... more In last two years according to the statistics extracted from periodic reports of Commercial Bank PLC (CBPLC) in Sri Lanka, the performance in term of Non-performing Advances (NPA) has been competitive although it indicated an upward trend. As a result, strong competitors such as Hatton National Bank PLC surpassed CBPLC to establish its position in the industry. CBPLC identified in investigations that NPA is one of the key factors which had an impact on this situation. It is observed the bank recorded a higher NPA ratio than other competitors in the industry in last few years. Therefore, the study has been structured to analyze the impact of NPA on profitability of Private commercial banks in Sri Lanka. The study is based on questionnaires answered by 114 credit and recovery officers of the bank selected on simple random sampling method. A descriptive analysis, Pearson's binary correlation analysis and factor analysis is used as statistical tools. Finally it is clear there is negative impact between independent variables and dependent variable. So, highest impact shows from risk credit management among selected independent variables. Next highest impact shows by recovery procedures and lowest impact shown by credit monitoring.
EPRA, 2019
The insurance industry in Sri Lanka has the goal to provide quality service to satisfy their cust... more The insurance industry in Sri Lanka has the goal to provide quality service to satisfy their customers in the principal
of severe competition for market share with its plentiful competitors. Sri Lankan insurance industry is regulated by
IRCSL and according to its records as at April 2018, the insurance industry was generally made up of 19 Non-Life
companies and 10 Life companies. The problem of this research is that how can effects the service quality on
customer satisfaction in Sri Lankan insurance industry. The population belongs to the research is life insurance
policy holders in Maharagama AGA Division in Sri Lanka and the researcher has selected 250 number of sample
using quota sampling method. Primary data is collected through structured questionnaires which consists three parts.
Tangibility, Reliability, Responsiveness, Empathy and Assurance measured using five point likert scale as indicators
of service quality. Validity analysis, Frequency analysis, Factor analysis, Descriptive statistics, Chi-squared test and
correlation analysis were used as analysis tools. It was identified that there is a relationship between customer
satisfaction with the demographic factors such as insurance company, gender, age group, occupation, monthly
income and also time period deal with current company while no relationship civil status, race, religion and also
education level. There is significant positive relationships between dependent variable named customer satisfaction
and independent variables named tangibility, reliability, responsiveness, empathy and assurance. The variable named
empathy shows the largest relationship with the customer satisfaction. Lowest relationship shows the variable named
tangibility.
KEYWORDS: Insurance industry, Customer satisfaction, Tangibility, Reliability, Responsiveness, Empathy,
Assurance
úYa júoHd, wOHdmkh i|yd rcfha jeh ls Íï mS ' Ô' ;drld kq jka ;s fmf¾rd 1 ixla fIa mh úYa júoHd, i... more úYa júoHd, wOHdmkh i|yd rcfha jeh ls Íï mS ' Ô' ;drld kq jka ;s fmf¾rd 1 ixla fIa mh úYa júoHd, i|yd flfrk rdcH úhou ms <s n| j iudcfha fnfyúka idlÉPdjg ,la flfrk wjêhl ta ms <s n|j lreKq úuid ne,S u jeo.;a h' miq .s h jir fod<y ;= < úYa júoHd, wOHdmkh i|yd rch is ÿlrk jeh ls Íï flfia fjkia ù ;s fí o" tu úp,khka g ;= vq ÿka fya ;= fudkjd o hka k wOHhkh ls Íu fuu ,s ms fha wruq K fõ' hï rgl úYa júoHd, wOHdmkh i|yd rch is ÿ lrk jeh ls Íï ms <s n| j wOHhkh ls Ífï oS la fIa ;% ls ys mhla ms <s n|j u wjOdkh fhduq l< hq ;= h' fuys oS tu la fIA ;% mokï lr .ks ñka 2002 j¾Ifha is g 2013 j¾Ih ola jd o;a ; Ndú;fhka ixLHdkuh úYa f,a IKhla is ÿ lr we;' YS % ,xldfõ rcfha wOHdmk moa O;s h úis ka ìys lrk udkj m% d.a Okfha .= Kd;a ulNdjh Y% u fjf<|fmd< wjYH;djhka g wkq l+ ,j fjkia ls Íug wjYH mßos kj oekq u ms <s n| ux fiùug yd th Y% u fjf<|fmdf<a .;s l wjYH;d iuÕ .e,mS u i|yd wdfhda ckh ls Íug wjYH moku oeóu i|yd fuu ld, iS udj ;= < rch úYa júoHd, wOHdmkhg oerE úhofuka úYd, fldgila jeh lr we;s nj meyeos ,s fõ' tf,iu rch úYa j úoHd,j,g is ÿ l< m% d.a Ok úhou l% u l% ufhka jeä ù we;s fyhs ka miq .s h oYlh ;= < úYa júoHd,j, m% d.a Ok iïm;a os hq Kq ls Íug rcfha jeä wjOdkhla fhduq lr we;s nj ks .ukh l< yels h' tfia u miq .s h oYlh ;= < iq NidOk lghq ;= i|yd is ¥ lrk úhou wvq ù we;;a wfkl= ;a j¾;k úhoï jeä ù we;' tla tla úYa júoHd,h i|yd rch ord we;s úhofï m% udKhka w;r úYd, jYfhka fjkia lï mj;S ' thg fya ;= j tu tla tla úYa júoHd,fha l% s hd;a ul jk Wmdê mdGud,djka m% udKh yd Ys IH ixLHdj tls fklg fjkia ùuhs ' iuia ;hla f,i .;a l, tla úYa júoHd, Ys IHfhl= fjkq fjka rch orK úhou 39'35]ls ka by< f.dia ;s fí' uq LH mo( úYa júoHd, wOHdmkh" rdcH úhou" Ys IH iq NidOkh ye|s ka ùu rgl wOHdmk wxYh hkq oekq u mokï lr .;a wd¾:s lhl ;s ridr by< j¾Ok fõ.hla mj;a jd .ekS ug wjYH oekq u we;s yd Y% u fjf<|fmdf<a 1 Ydia ;% fõoS ^úfYa I& iudc ixLHdkh f;jk jir"
Conference Presentations by THARAKA N . PERERA
ICASS, 2019
Introduction
The generation of Domestic Solid Waste (DSW) has become a growing environmental and... more Introduction
The generation of Domestic Solid Waste (DSW) has become a growing environmental and public health problem, specifically in developing countries (Bandara et al, 2007). So the DSW management is a significant role of urban authorities and it is straightly interrelated with the protection of environmental wellbeing and human health and also it is indirectly interrelated with living standards of people. The rapid increase in solid waste generation due to accelerated urban population growth, unplanned urbanization, and increasing economic activities, has become a crucial problem in all countries regardless of the development status of them (Kwetey, 2014). With the current stage of rapid urbanization, relevant authorities in Sri Lanka are also suffering serious difficulties in addressing this problem. The waste generation amount in Sri Lanka has increased from around 6,400 ton/day in 1999 to 10,786 ton/day since 2009 due to the economic growth after the end of the civil war (JICA, 2016). According to critical view of literature, there are lack of preliminary and regular study has been conducted in Sri Lanka on this concerns. Sri Lanka does not drawing attention to this problem may be heightened in the future in many folds than it is today unless alternatives are designed to address it and also findings of this study can be used to get information to implement the management system for solid waste.
Research Problem
The generation of DSW has become a growing environmental and public health issue. Generation of DSW is the path to generation of municipal solid waste which became a highest socio economical and health issue in developing countries. So the research problem of this study is to find what are the major socio economic factors that affecting the DSW generation in Sri Lanka.
Methodology
This research used both primary and secondary data. Primary data were collected from 84 households situated in Kesbewa municipal area using stratified random sampling method with the structured questionnaire and interviews during the period from 5th March to 28th March, 2016. Secondary data gained from the final report of the data collection survey on solid waste management in democratic socialist republic of Sri Lanka. Kesbewa municipal area has selected as study area because although there are some solid waste management programs, urban council has quite failed to formulate any master plan or action plan related to solid waste management and also there is Karadiyana waste processing project in the Kesbewa municipal area.
Correlation analysis and regression analysis were used as analyzing tool of this study. The variables has defined based on the research done by Sankoh et al in 2012. Accordingly, the Ordinary Least Square regression model is used to study the percentage of solid waste generated by household per day (Y) on the household income (x1), size of the household (x2), extra land size within the compound of the household (x3), distance from the center of the city (x4) and the gender of household head (x5) (Sankoh et al, 2012). Regression model which used to analysis purposes can be derived as below.
Y= β_0+ β_1 x_1+β_2 x_2+β_3 x_3+β_4 x_4+β_5 x_5+ U_i
Results and Discussion
According to the survey results, average amount of solid waste generated by households is 2.18 kg / day. Table 1 shows the results of the correlation analysis.
Table 1: Correlation coefficients of determinants of solid waste generation
Y Coefficient t value P value
Income 0.912 3.71 0.001***
Size of H/H 0.991 2.91 0.011**
Extra land -0.502 -2.06 0. 027**
Distance 0.408 0.22 0.811
Gender 0.688 1.01 0.322
Note: *, **, *** represent the significant at 10 %, 5 % and 1 % respectively
According to the Table 1, major socio economic factors which has higher positive relationship with the DSW generation are household income and household size while extra land has higher negative relationship with the DSW generation. Distance from the center of the city and gender of the household are not have any significant relationship on waste generation.
Table 2 shows the results of the regression analysis of the gathered data of this study.
Table 2: Regression coefficients of determinants of solid waste management
Y Coefficient t value P value
Constant 3.208 1.01 0.322
Income 3.412 4.23 0.001***
Size of H/H 4.213 3.91 0.001***
Extra land -2.105 -2.17 0. 024**
Distance 1.369 0.97 0.417
Gender 0.598 1.48 0.301
Note: *, **, *** represent the significant at 10 %, 5 % and 1 % respectively
As per Table 2, major socio economic factors which impact the household solid waste generation are household income, size of household and the extra land size. The distance to the house from the center of the city and gender of the household are not have any significant impact on DSW generation. Size of the household is the most important factor and household’s income has a significant positive impact on household solid waste generation.
Conclusion
This study identifies household income, size of household and extra land size are the major determinants of DSW generation. Households which have larger income are tend to generate more solid waste and also if the size of household is larger, those households are tend to generate more solid waste. The house-holds which have more extra land as compound they are less tend to generate DSW. Further, according to respondents’ opinions it should be increase the efficiency of collecting solid waste and also it should increase the frequent of the collecting solid waste. Nevertheless introducing a service fee for the waste management service provided by Kesbewa municipal council have been recommended by respondents. In the case of further research it could expand to some other municipal areas and get generalized conclusion, it will be very useful for the policy implementation on DSW management.
Key words: Municipal area; Socio-economic Determinants; Solid Waste Generation; Solid Waste Management.
ICMA, 2019
Real Effective Exchange Rate (REER) is a measure of the trade-weighted average exchange rate of a... more Real Effective Exchange Rate (REER) is a measure of the trade-weighted average exchange rate of a currency against a basket of currencies after adjusting for inflation differentials with regard to the countries concerned and expressed as an index number relative to a base year. Inflation, Interest Rate, Speculation, Balance of Payment (BOP) and Economic Growth are some factors which affect REER. Balance of Payment (BOP) is the record of all international trade and financial transactions made by a country's residents. Previous studies have stated that exchange rate depends on joint dynamic behaviour of different Balance of Payment components: Balance of Payment affect the exchange rate of a country. The problem of this study was to check whether there is a significant impact of BOP on REER in Sri Lanka during a considerable period. Accordingly, objectives of this study were to examine the long-run and short-run impact of BOP on REER in Sri Lanka and also to identify the behaviour of REER and BOP through a considerable period. The quarterly time-series data of REER (2010= 100 Index) and BOP (US million dollars) were carried out from 2001 to 2016 from quarterly reports of the Central Bank of Sri Lanka. Two Lag ARDL Model was estimated, and the model fulfilled the requirements which have a statistically significant model such as Akaike info criterion and Schwarz criterion, Johansen test of co integration, serial correlation test, Cusum test, Bound test, R 2. According to the results of the current study, there is a long-term association in REER and BOP which confirm the results of the previous studies. BOP shows a small amount of significant impact on REER. Speed of Adjustment in the whole system towards the long-term equilibrium is 19.6%.
The 20th International Postgraduate Research Conference, 2019
One of the major essentials in improving efficiency in the provision of health care services is p... more One of the major essentials in improving efficiency in the provision of health care services is patient flow. The growing population and health-need due to adverse environmental conditions have led to escalating waiting times and crowding in government hospitals. Queuing theory has effectively been applied to various fields including health care. According to the previous literature, the application of queuing theory enhanced the efficiency of the waiting time of both dentists and patients. As a developing country, Sri Lankan government hospitals also face the challenge of queuing problems. The problem of this study is identifying an appropriate queuing model to enhance the efficiency of waiting time in the Dental clinic in Colombo South Teaching Hospital (CSTH). This study has used the secondary data obtained through the annual bulletin of Colombo South Teaching Hospital Statistic unit, Hospital data Queries and also primary data were obtained by the direct observations and structured questionnaire within January 2019. In the analysis purpose, this study mainly used queuing approach with M/M/1, M/M/S, M/M/S/N systems and the service disciplines like first come first out, priority and shortest job first. Under these queuing models, study has calculated the various parameters to measure the queue performance in a dental clinic in the CSTH. In this case study use M/M/4 queue model to characterize the patient flow in the Dental clinic of CSTH and M/M/S/N system characterized at the light surgery section of the dental. Under these queuing models, this study has measured various parameters such as Utilization factor, Average queue length, Average number of system, Average waiting time in the queue, Average waiting time in the system, Idle time of the servers and Probability of exactly n customers in the system, etc. The Multiple Single-Server queuing model is employed at the dental clinic. This implies that patients on arrival to the clinic join a queue to see any out of about 3 to 5 doctors who are consulting at the same time. All dentists have a single line of patients waiting to be attended to and the patients are directed to the queues by the nurses and record staff of the clinic. The patients are directed to queues in the order they arrived. This study has considered that the number of dentists is less than with the number of beds. Practice shows that the majority of the cases the dentists can deal with more than 1 patient in 25 minutes. Some of the suggestions from patients included more dentists be employed to reduce waiting time on the queue, doctors need to come on time to avoid stagnation of patients at the clinic, first-come-first-serve discipline should be observed on the queue to ensure fair play, and records staff should not take bribe from patients for the purpose of jumping the queue. Queues should arrange on the aspect of service provided by each dentist.
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Papers by THARAKA N . PERERA
Aging population, which results from rapid demographic transition, is a key global demographic challenge which will continue as an issue in both developed and developing nations during the twenty-first century (Niessen & Gibsen, 2000; Ettinger, 1997). Sri Lanka is the first country which reached demographic transition among the South Asian countries and Sri Lanka reports the highest aging population among South Asian countries as percentage (Menike, 2014). Therefore, Sri Lanka is rapidly experiencing aging problem. As a developing country Sri Lanka has faced socio-economic issues and challenges related to population ageing and aging population is burden to the government (Perera, 2017). As a result of increasing load of aging population, there is rapid increasing the number of enrolment to elders’ home (Luo, Xue & Zhang, 2018). If the study can identify the factors influencing aging populations’ intention to enroll in elders’ homes, it would be significant for get decisions on aging populations’ well-being.
Research Objectives
1. Identify the demographic factors influencing the intention of aging population in enrolling to elders’ homes.
2. Identify the social factors influencing the intention of aging population in enrolling to elders’ home.
Methodology
A sample of 40 elders from two elders’ home in Kesbewa AGA division is selected for this sample survey (2019) using convenience sampling technique. Researcher used convenience sampling technique to select the sample for this study and sample size limit to 40 elders. Structured interview technique is used to gather primary data and secondary data from previous literature is also used to identify trends of aging population’s intention to enroll in elders’ homes. Gender, marital status,
race, religion, monthly family income, number of family members, occupation and level of education are consider as demographic factors. On the other hand avoiding suffer and worries, no one care after them, economic difficulties and avoidance of children are consider as social factors. Analysis purposes frequency analysis used to identify the social factors and one sample chi square test as non-parametric statistics used to identify the significant demographic factors. Researcher build hypotheses as the categories of each demographic factor occur with equal probabilities. If the null hypothesis reject, it can conclude that demographic factor is significantly influencing the intention of aging population in enrolling to elders’ home.
Results and discussion
It is better to get idea on demographic characteristics of the sample, before it identify the demographic factors influencing the intention of aging population in enrolling to elders’ homes.
of severe competition for market share with its plentiful competitors. Sri Lankan insurance industry is regulated by
IRCSL and according to its records as at April 2018, the insurance industry was generally made up of 19 Non-Life
companies and 10 Life companies. The problem of this research is that how can effects the service quality on
customer satisfaction in Sri Lankan insurance industry. The population belongs to the research is life insurance
policy holders in Maharagama AGA Division in Sri Lanka and the researcher has selected 250 number of sample
using quota sampling method. Primary data is collected through structured questionnaires which consists three parts.
Tangibility, Reliability, Responsiveness, Empathy and Assurance measured using five point likert scale as indicators
of service quality. Validity analysis, Frequency analysis, Factor analysis, Descriptive statistics, Chi-squared test and
correlation analysis were used as analysis tools. It was identified that there is a relationship between customer
satisfaction with the demographic factors such as insurance company, gender, age group, occupation, monthly
income and also time period deal with current company while no relationship civil status, race, religion and also
education level. There is significant positive relationships between dependent variable named customer satisfaction
and independent variables named tangibility, reliability, responsiveness, empathy and assurance. The variable named
empathy shows the largest relationship with the customer satisfaction. Lowest relationship shows the variable named
tangibility.
KEYWORDS: Insurance industry, Customer satisfaction, Tangibility, Reliability, Responsiveness, Empathy,
Assurance
Conference Presentations by THARAKA N . PERERA
The generation of Domestic Solid Waste (DSW) has become a growing environmental and public health problem, specifically in developing countries (Bandara et al, 2007). So the DSW management is a significant role of urban authorities and it is straightly interrelated with the protection of environmental wellbeing and human health and also it is indirectly interrelated with living standards of people. The rapid increase in solid waste generation due to accelerated urban population growth, unplanned urbanization, and increasing economic activities, has become a crucial problem in all countries regardless of the development status of them (Kwetey, 2014). With the current stage of rapid urbanization, relevant authorities in Sri Lanka are also suffering serious difficulties in addressing this problem. The waste generation amount in Sri Lanka has increased from around 6,400 ton/day in 1999 to 10,786 ton/day since 2009 due to the economic growth after the end of the civil war (JICA, 2016). According to critical view of literature, there are lack of preliminary and regular study has been conducted in Sri Lanka on this concerns. Sri Lanka does not drawing attention to this problem may be heightened in the future in many folds than it is today unless alternatives are designed to address it and also findings of this study can be used to get information to implement the management system for solid waste.
Research Problem
The generation of DSW has become a growing environmental and public health issue. Generation of DSW is the path to generation of municipal solid waste which became a highest socio economical and health issue in developing countries. So the research problem of this study is to find what are the major socio economic factors that affecting the DSW generation in Sri Lanka.
Methodology
This research used both primary and secondary data. Primary data were collected from 84 households situated in Kesbewa municipal area using stratified random sampling method with the structured questionnaire and interviews during the period from 5th March to 28th March, 2016. Secondary data gained from the final report of the data collection survey on solid waste management in democratic socialist republic of Sri Lanka. Kesbewa municipal area has selected as study area because although there are some solid waste management programs, urban council has quite failed to formulate any master plan or action plan related to solid waste management and also there is Karadiyana waste processing project in the Kesbewa municipal area.
Correlation analysis and regression analysis were used as analyzing tool of this study. The variables has defined based on the research done by Sankoh et al in 2012. Accordingly, the Ordinary Least Square regression model is used to study the percentage of solid waste generated by household per day (Y) on the household income (x1), size of the household (x2), extra land size within the compound of the household (x3), distance from the center of the city (x4) and the gender of household head (x5) (Sankoh et al, 2012). Regression model which used to analysis purposes can be derived as below.
Y= β_0+ β_1 x_1+β_2 x_2+β_3 x_3+β_4 x_4+β_5 x_5+ U_i
Results and Discussion
According to the survey results, average amount of solid waste generated by households is 2.18 kg / day. Table 1 shows the results of the correlation analysis.
Table 1: Correlation coefficients of determinants of solid waste generation
Y Coefficient t value P value
Income 0.912 3.71 0.001***
Size of H/H 0.991 2.91 0.011**
Extra land -0.502 -2.06 0. 027**
Distance 0.408 0.22 0.811
Gender 0.688 1.01 0.322
Note: *, **, *** represent the significant at 10 %, 5 % and 1 % respectively
According to the Table 1, major socio economic factors which has higher positive relationship with the DSW generation are household income and household size while extra land has higher negative relationship with the DSW generation. Distance from the center of the city and gender of the household are not have any significant relationship on waste generation.
Table 2 shows the results of the regression analysis of the gathered data of this study.
Table 2: Regression coefficients of determinants of solid waste management
Y Coefficient t value P value
Constant 3.208 1.01 0.322
Income 3.412 4.23 0.001***
Size of H/H 4.213 3.91 0.001***
Extra land -2.105 -2.17 0. 024**
Distance 1.369 0.97 0.417
Gender 0.598 1.48 0.301
Note: *, **, *** represent the significant at 10 %, 5 % and 1 % respectively
As per Table 2, major socio economic factors which impact the household solid waste generation are household income, size of household and the extra land size. The distance to the house from the center of the city and gender of the household are not have any significant impact on DSW generation. Size of the household is the most important factor and household’s income has a significant positive impact on household solid waste generation.
Conclusion
This study identifies household income, size of household and extra land size are the major determinants of DSW generation. Households which have larger income are tend to generate more solid waste and also if the size of household is larger, those households are tend to generate more solid waste. The house-holds which have more extra land as compound they are less tend to generate DSW. Further, according to respondents’ opinions it should be increase the efficiency of collecting solid waste and also it should increase the frequent of the collecting solid waste. Nevertheless introducing a service fee for the waste management service provided by Kesbewa municipal council have been recommended by respondents. In the case of further research it could expand to some other municipal areas and get generalized conclusion, it will be very useful for the policy implementation on DSW management.
Key words: Municipal area; Socio-economic Determinants; Solid Waste Generation; Solid Waste Management.
Aging population, which results from rapid demographic transition, is a key global demographic challenge which will continue as an issue in both developed and developing nations during the twenty-first century (Niessen & Gibsen, 2000; Ettinger, 1997). Sri Lanka is the first country which reached demographic transition among the South Asian countries and Sri Lanka reports the highest aging population among South Asian countries as percentage (Menike, 2014). Therefore, Sri Lanka is rapidly experiencing aging problem. As a developing country Sri Lanka has faced socio-economic issues and challenges related to population ageing and aging population is burden to the government (Perera, 2017). As a result of increasing load of aging population, there is rapid increasing the number of enrolment to elders’ home (Luo, Xue & Zhang, 2018). If the study can identify the factors influencing aging populations’ intention to enroll in elders’ homes, it would be significant for get decisions on aging populations’ well-being.
Research Objectives
1. Identify the demographic factors influencing the intention of aging population in enrolling to elders’ homes.
2. Identify the social factors influencing the intention of aging population in enrolling to elders’ home.
Methodology
A sample of 40 elders from two elders’ home in Kesbewa AGA division is selected for this sample survey (2019) using convenience sampling technique. Researcher used convenience sampling technique to select the sample for this study and sample size limit to 40 elders. Structured interview technique is used to gather primary data and secondary data from previous literature is also used to identify trends of aging population’s intention to enroll in elders’ homes. Gender, marital status,
race, religion, monthly family income, number of family members, occupation and level of education are consider as demographic factors. On the other hand avoiding suffer and worries, no one care after them, economic difficulties and avoidance of children are consider as social factors. Analysis purposes frequency analysis used to identify the social factors and one sample chi square test as non-parametric statistics used to identify the significant demographic factors. Researcher build hypotheses as the categories of each demographic factor occur with equal probabilities. If the null hypothesis reject, it can conclude that demographic factor is significantly influencing the intention of aging population in enrolling to elders’ home.
Results and discussion
It is better to get idea on demographic characteristics of the sample, before it identify the demographic factors influencing the intention of aging population in enrolling to elders’ homes.
of severe competition for market share with its plentiful competitors. Sri Lankan insurance industry is regulated by
IRCSL and according to its records as at April 2018, the insurance industry was generally made up of 19 Non-Life
companies and 10 Life companies. The problem of this research is that how can effects the service quality on
customer satisfaction in Sri Lankan insurance industry. The population belongs to the research is life insurance
policy holders in Maharagama AGA Division in Sri Lanka and the researcher has selected 250 number of sample
using quota sampling method. Primary data is collected through structured questionnaires which consists three parts.
Tangibility, Reliability, Responsiveness, Empathy and Assurance measured using five point likert scale as indicators
of service quality. Validity analysis, Frequency analysis, Factor analysis, Descriptive statistics, Chi-squared test and
correlation analysis were used as analysis tools. It was identified that there is a relationship between customer
satisfaction with the demographic factors such as insurance company, gender, age group, occupation, monthly
income and also time period deal with current company while no relationship civil status, race, religion and also
education level. There is significant positive relationships between dependent variable named customer satisfaction
and independent variables named tangibility, reliability, responsiveness, empathy and assurance. The variable named
empathy shows the largest relationship with the customer satisfaction. Lowest relationship shows the variable named
tangibility.
KEYWORDS: Insurance industry, Customer satisfaction, Tangibility, Reliability, Responsiveness, Empathy,
Assurance
The generation of Domestic Solid Waste (DSW) has become a growing environmental and public health problem, specifically in developing countries (Bandara et al, 2007). So the DSW management is a significant role of urban authorities and it is straightly interrelated with the protection of environmental wellbeing and human health and also it is indirectly interrelated with living standards of people. The rapid increase in solid waste generation due to accelerated urban population growth, unplanned urbanization, and increasing economic activities, has become a crucial problem in all countries regardless of the development status of them (Kwetey, 2014). With the current stage of rapid urbanization, relevant authorities in Sri Lanka are also suffering serious difficulties in addressing this problem. The waste generation amount in Sri Lanka has increased from around 6,400 ton/day in 1999 to 10,786 ton/day since 2009 due to the economic growth after the end of the civil war (JICA, 2016). According to critical view of literature, there are lack of preliminary and regular study has been conducted in Sri Lanka on this concerns. Sri Lanka does not drawing attention to this problem may be heightened in the future in many folds than it is today unless alternatives are designed to address it and also findings of this study can be used to get information to implement the management system for solid waste.
Research Problem
The generation of DSW has become a growing environmental and public health issue. Generation of DSW is the path to generation of municipal solid waste which became a highest socio economical and health issue in developing countries. So the research problem of this study is to find what are the major socio economic factors that affecting the DSW generation in Sri Lanka.
Methodology
This research used both primary and secondary data. Primary data were collected from 84 households situated in Kesbewa municipal area using stratified random sampling method with the structured questionnaire and interviews during the period from 5th March to 28th March, 2016. Secondary data gained from the final report of the data collection survey on solid waste management in democratic socialist republic of Sri Lanka. Kesbewa municipal area has selected as study area because although there are some solid waste management programs, urban council has quite failed to formulate any master plan or action plan related to solid waste management and also there is Karadiyana waste processing project in the Kesbewa municipal area.
Correlation analysis and regression analysis were used as analyzing tool of this study. The variables has defined based on the research done by Sankoh et al in 2012. Accordingly, the Ordinary Least Square regression model is used to study the percentage of solid waste generated by household per day (Y) on the household income (x1), size of the household (x2), extra land size within the compound of the household (x3), distance from the center of the city (x4) and the gender of household head (x5) (Sankoh et al, 2012). Regression model which used to analysis purposes can be derived as below.
Y= β_0+ β_1 x_1+β_2 x_2+β_3 x_3+β_4 x_4+β_5 x_5+ U_i
Results and Discussion
According to the survey results, average amount of solid waste generated by households is 2.18 kg / day. Table 1 shows the results of the correlation analysis.
Table 1: Correlation coefficients of determinants of solid waste generation
Y Coefficient t value P value
Income 0.912 3.71 0.001***
Size of H/H 0.991 2.91 0.011**
Extra land -0.502 -2.06 0. 027**
Distance 0.408 0.22 0.811
Gender 0.688 1.01 0.322
Note: *, **, *** represent the significant at 10 %, 5 % and 1 % respectively
According to the Table 1, major socio economic factors which has higher positive relationship with the DSW generation are household income and household size while extra land has higher negative relationship with the DSW generation. Distance from the center of the city and gender of the household are not have any significant relationship on waste generation.
Table 2 shows the results of the regression analysis of the gathered data of this study.
Table 2: Regression coefficients of determinants of solid waste management
Y Coefficient t value P value
Constant 3.208 1.01 0.322
Income 3.412 4.23 0.001***
Size of H/H 4.213 3.91 0.001***
Extra land -2.105 -2.17 0. 024**
Distance 1.369 0.97 0.417
Gender 0.598 1.48 0.301
Note: *, **, *** represent the significant at 10 %, 5 % and 1 % respectively
As per Table 2, major socio economic factors which impact the household solid waste generation are household income, size of household and the extra land size. The distance to the house from the center of the city and gender of the household are not have any significant impact on DSW generation. Size of the household is the most important factor and household’s income has a significant positive impact on household solid waste generation.
Conclusion
This study identifies household income, size of household and extra land size are the major determinants of DSW generation. Households which have larger income are tend to generate more solid waste and also if the size of household is larger, those households are tend to generate more solid waste. The house-holds which have more extra land as compound they are less tend to generate DSW. Further, according to respondents’ opinions it should be increase the efficiency of collecting solid waste and also it should increase the frequent of the collecting solid waste. Nevertheless introducing a service fee for the waste management service provided by Kesbewa municipal council have been recommended by respondents. In the case of further research it could expand to some other municipal areas and get generalized conclusion, it will be very useful for the policy implementation on DSW management.
Key words: Municipal area; Socio-economic Determinants; Solid Waste Generation; Solid Waste Management.