Selected socio-economic factors affecting the ...

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Selected socio-economic factors affecting the willingness to minimise solid waste in Dhaka city, Bangladesh a

b

c

Rafia Afroz , Rabaah Tudin , Keisuke Hanaki & Muhammad Mehedi Masud

a

a

Department of Economics, Faculty of Economics and Management Science, International Islamic University Malaysia, Kuala Lumpur, 50728, Malaysia b

Department of Economics, Faculty of Economics and Business, University Malaysia Sarawak c

Department of Urban Engineering, Faculty of Engineering, The University of Tokyo, Japan Published online: 17 Jun 2011.

To cite this article: Rafia Afroz , Rabaah Tudin , Keisuke Hanaki & Muhammad Mehedi Masud (2011): Selected socio-economic factors affecting the willingness to minimise solid waste in Dhaka city, Bangladesh, Journal of Environmental Planning and Management, 54:6, 711-731 To link to this article: http://dx.doi.org/10.1080/09640568.2010.527472

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Journal of Environmental Planning and Management Vol. 54, No. 6, July 2011, 711–731

Selected socio-economic factors affecting the willingness to minimise solid waste in Dhaka city, Bangladesh Rafia Afroza*, Rabaah Tudinb, Keisuke Hanakic and Muhammad Mehedi Masuda


a Department of Economics, Faculty of Economics and Management Science, International Islamic University Malaysia, Kuala Lumpur 50728, Malaysia; bDepartment of Economics, Faculty of Economics and Business, University Malaysia Sarawak; cDepartment of Urban Engineering, Faculty of Engineering, The University of Tokyo, Japan

(Received 30 September 2009; final version received 24 September 2010) This paper examines the factors that influence the waste generation and willingness to minimise solid waste in Dhaka city, Bangladesh. Information on waste generation, willingness to minimise, socio-economic characteristics, and behaviour of the households towards solid waste management were obtained from interviews with 402 households in Dhaka city. Of these, 103 households regularly practised recycling activities. Ordinary least square (OLS) regression and logistic regression analysis were used to determine the dominant factors that might influence the waste generation and households’ willingness to minimise solid waste, respectively. The results found that the waste generation of the households in Dhaka city was significantly affected by environmental consciousness, income groups, particularly the middle-income earners, and willingness to separate. The significant factors for willingness to minimise solid waste were environmental consciousness, income groups particularly the middle-income earners, young adults mainly those aged between 25 to 35 years and storage facility. Establishment of a solid waste management programme could be an effective strategy for implementing sustainable waste management in Bangladesh. For this strategy to succeed, however, active partnership between the respondents and waste management service department is required. The respondents’ behaviour toward solid waste management practices should be taken into consideration, as should the results of this study, which are important indicators of respondents’ positive attitudes toward sustainable waste management in Dhaka city. Keywords: waste minimisation; waste generation; recycling; logistic regression model; perception and attitude

1.

Introduction

Urban solid waste management is considered to be one of the most serious environmental problems confronting urban areas in developing countries (Pfammatter and Schertenleib 1996, WRI 1996, Sinha and Enayetullah 2000), and Bangladesh is no exception. Bangladesh has the highest density of population of all countries of the world. It has very little open physical space and empty terrain to cushion the country against environmental shocks. Therefore, any environmental

*Corresponding author. Email: rafi[email protected] ISSN 0964-0568 print/ISSN 1360-0559 online Ó 2011 University of Newcastle upon Tyne DOI: 10.1080/09640568.2010.527472 http://www.informaworld.com


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contagion in Bangladesh is sure to spread very fast and affect millions of people (Salequzzaman and Stocker 2001). If the population increases, resource consumption also increases as a side effect (Haden et al. 2009), and the highest population has the highest generation of waste (Ayotamuno and Gobo 2004). Urbanisation in Bangladesh is no different to what has happened in China, where urban migration has become a burden to economic development and a problem for the environment (Ling and Isaac 1996). Bangladesh’s population density is already 50 times higher than that of the USA, six times higher than that of China, and the country is the worst victim of environmental degradation, therefore, protection of the environment is necessary even from the view of social justice (Salequzzaman and Stocker 2001). Dhaka, the capital city of Bangladesh, with more than 10 million inhabitants, is one of the fastest growing mega cities in the world. In the period from 1991 to 2004, Dhaka’s population had an average of more than 4% annual growth rate (DOE 2004). The Dhaka metropolitan area occupies approximately 1353 km2 (Enayetullah and Sinha 1999). Approximately 6 million residents live under the management of Dhaka city corporation (DCC), covering an area of 344 km2 (Enayetullah and Sinha 1999). In Dhaka, solid waste generation amounts to 3500 ton/day, of which 1800 tons are collected and dumped by the Dhaka city corporation (DCC), 900 tons end up in backyards and informal landfills, 400 tons end up on roadsides or open space, 300 tons are recycled by the Tokais (destitute slum children acting as scavengers), and 100 tons go through informal recycling at the point of generation (DCC 2005). Irrespective of the municipal authorities’ ability to collect it, both collected and uncollected waste creates problems for the city residents. A household awareness survey was conducted by DCC in 2004 in Dhaka city, which found that 88% of the upper-income group, 95% of the middle-income group and 100% of the lowerincome group were not willing to participate in recycling activities. Unfortunately, public participation in waste management (including waste minimisation) in developing countries, including Dhaka, is very low. The general situation of poverty and illiteracy of the masses makes Bangladesh very vulnerable to environmental damage, and the general populace of Bangladesh is too busy trying to meet their basic material needs, therefore they have little scope to be concerned about environmental amenities (Salequzzaman and Stocker 2001). The Summary Report (BBS 1995) shows that 46.7% of the urban population (14.5 million) lives in absolute poverty and in Dhaka some 40 to 45% of the people live in slums and slum-like areas (Zuberi 1998). A number of homeless individuals make the road their home, while some use boxes as their shelter which they call home, and some people consider these ‘boxes’ as waste. Alternatively, low-income households have too little to recycle, and middle-income households might have no space in their homes to keep recycled materials so they have few incentives to manage waste. In addition, at present no structured recycling mechanism is being implemented for households in Dhaka. Many people do not know the location of the nearest collection point. Knowledge of the location of collection points is poor or they are too far away, so it easier to throw the recyclables into the street than to bring them to a collection point (Sujauddin et al. 2008). Finding adequate waste disposal sites for the future is also very difficult at present considering the increased population and horizontal expansion of the city. Overall, the city corporations have failed to manage the solid waste of this increasing population, mainly because of a lack of financial support and willingness to pay (WTP) and low participation of the households for


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overall sustainable solid waste management policies. Therefore, there is an urgent requirement to increase public awareness of the waste minimisation problem and to estimate the factors that are responsible for the increasing generation of waste. Identification of these factors would be helpful for the environmental and waste management planners in their decision making for managing waste and environmental pollution. A considerable amount of research work on solid waste management has already been conducted in Bangladesh (Salequzzaman et al. 1998, 2001, Salequzzaman 2000, Ahmed and Rahman 2000, Alam et al. 2002, Hasan and Chowdhury 2005, Enayetullah et al. 2005, Rahman et al. 2006, Sinha 2006). However, so far no study has yet been undertaken which investigates the effect of the socio-economic level of householders on solid waste generation and minimisation. The objectives of the current study were, therefore, to contribute to a better understanding of household waste management behaviour by examining waste management practices and behaviours of the residents of Dhaka city, Bangladesh. More specifically, it analyses the factors that promote a household’s waste generation and their willingness to minimise the household waste. The results of the study will provide inputs into the formulation of local waste minimisation plans and programmes, particularly on waste segregation and recycling activities of the residents of Dhaka city, Bangladesh. 2. Methodology 2.1. Theoretical framework for waste generation of the households In developing an effective waste minimisation strategy for a given region, it is important to know the amount of waste generated and the composition of the waste stream as these have direct effects on the socio-economic factors. In the past, economists discussed the socio-economic factors influencing household waste generation. Viewed from an economic perspective, Wertz (1976) analysed household behaviour with regard to waste generation in terms of changes in income, price of a refuse service, frequency of the service, site of refuse collection and packaging. Household size, cultural patterns, education and personal attitudes (Grossmann et al. 1974, Al-Momani 1994) also influence solid waste generation. Economists have also compared the composition and quantity of waste in terms of income level, household size and age structure of the household as these affect the quantity and composition of solid waste. For example, the study by Richardson and Havlicek (1978) showed that grass, yard wastes and the newspaper that people read were positively correlated with the level of income. Hence the current project considers age, education, knowledge, income, household size and extra land as important components that affect the solid waste generation. Maturity of the respondents might affect their attitude towards environmental issues. In a poor country, if a household includes teenagers, they might not consider environmental issues as their priority in life compared to retired people who spend many hours taking care of their home. Similarly, level of education affects the way people lead their lives. A person with a higher level of education will most probably be more articulate and undertake analytical reasoning. Ling and Isaac (1996) conducted research in China, and they claimed that national awareness relating to environmental protection needs to be stimulated by education. Ignorance and poverty were recognised as being responsible for the acceptance of toxic/hazardous wastes from industrialised countries (Sangodoyin and Ipadeola 2000). An informed


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population will mean that measures of environmental protection can be easily implemented (Ling and Isaac 1996). Education, training and research in the field of environment management is necessary (Zuberi 1998). Environmental education and care is not new in Bangladesh, however, the large majority of people in Bangladesh have had no chance to go through formal education; they have been using their own devices to cope with the environmental problems (Salequzzaman and Stocker 2001). The illiteracy only aggravates Bangladesh’s environmental problem because it acts as a barrier for them even to understand the damaging impact on their own physical and mental health of the environmental degradation that is occurring in their immediate environment (Salequzzaman and Stocker 2001). Thus, inclusion and dissemination of environmental knowledge and information in the formal and non-formal systems of education and the media should be ensured (Salequzzaman and Stocker 2001). Information and facts about the past, present and possible future scenario should be presented to the public. Research by Barr et al. (2001) indicated that recycling behaviour is influenced by convenience, knowledge and access to a kerbside scheme, whereas waste minimisation behaviour is driven more by a concern about environmental issues. For many people, income will determine what they buy, when they buy, where they buy and how frequently they buy the products. If income is low, most items purchased will probably be items of necessity, but those with high incomes will buy luxury and non-essential items. Thus, there is a positive relation between income and waste generation (Nilanthi et al. 2006). Sangodoyin and Ipadeola (2000) investigated environmental issues in Nigeria, and the waste produced differs according to the level of household income. Size of the household is associated with the population of a country. When the size of households increases, the country’s population will directly increase. The quickening pace of development, industrialisation, urbanisation and population growth in Bangladesh increase the environmental challenges (Salequzzaman and Stocker 2001). Various authors have shown that the amount of waste generated by a country is proportional to its population, and the mean living standards of the people (Wertz 1976, Grossmann et al. 1974, Medina 1997) relate to their income levels, hence the generation of individual household waste is correlated. For example, the average rate of waste generation in Port Harourt is approximately 1.25 kg/persons/household per annum (Ayotamuno and Gobo 2004). As a city grows in population and physical size, so its land use becomes more complex (Ayotamuno and Gobo 2004). For example, with the cultivation of land come the negative effects of extensive deforestation (Haden et al. 2009). As the land use becomes more complex, the solid waste generated increases in volume and variety (Ayotamuno and Gobo 2004). Extra land can also be used as storage or warehouses for unused or unwanted products. This study examines household waste generation using a multiple regression model considering the studies discussed above. 2.2. Theoretical framework for waste minimisation Willingness to pay for waste management services or facilities is very important to the success of participation by the private sector in solid waste management programmes. The willingness to pay or not to pay could have a direct impact (positive or negative) on the reliability and success of any solid waste management strategy (Epp and Mauger 1989, Rahman et al. 2006).



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This is, therefore, a question of demand or economics of household waste management, especially in a developing country such as Bangladesh. Household demand for solid waste services is a function of the unit price of solid waste services and other determining factors such as wage, non-wage income, prices of consumption goods, prices received for recyclables, waste components of market goods and quantity of waste generated by non-market goods (Jenkins 1993). Other socio-economic characteristics are included in models such as household size, age and education. The variables income and household size are surrogates for the unobserved household production activities which generate waste as a by-product (Hong et al. 1993). Some researchers have used this demand for solid waste services as a framework to model the determinants of household waste recycling (Hong et al. 1993, Reschovsky and Stone 1994, Jenkins et al. 2000). Jenkins et al. 2000 examined the intensity of recycling different waste materials using an ordered probit model, where the dependent variable, i.e. intensity of recycling each material (categorised at three levels), is a function of unit price of waste disposal, some characteristics of the local waste management system, and socio-economic factors such as household income, age and homeownership. Using the same model, Hong et al. 1993 modelled household recycling participation or the number of times it recycles over a period of time (categorised at five levels) as a function of disposal price and socio-economic variables. Finally, using a simple probit model, Reschovsky and Stone (1994) examined the probability of recycling a specific material and included socioeconomic variables and characteristics of recycling programmes as independent variables. The first two models examined mainly the influence of waste disposal price on household recycling behaviour, while the third model examined the differential effects of recycling systems when combined with unit pricing. Research on waste recycling in the developing world places less emphasis on understanding the indirect motives of a person’s behaviour (i.e. the recycling research focus in developed countries), but more emphasis on the practical, direct factors influencing the institutions and elements associated with waste management. Studies conducted in developing countries such as Malaysia, China and Mexico have found that recycling activities are further influenced by the availability of storage space in the home, the presence of recycling agents and the proximity of collection centres to households. It has also been observed that competencies were the best predictors of actual behaviour, whereas beliefs were more indicative of perceptions of behaviour or desired behaviour. In the case of recycling, a person was more likely to recycle waste when they fully understood the correct methods and the reasons to do it as opposed to simply having a desire to recycle (Corral-Verdugo 1997, Harvie and Jaques 2003). The present study examines household waste minimisation behaviour using binary choice modelling following the studies discussed above. Waste minimisation is an activity undertaken to facilitate recycling and disposal and thus entails household resources such as time, space and effort in the same manner as waste recycling. This household activity basically consists of the separation or sorting of wastes into recyclables and non-recyclables, and storing these wastes in separate containers to facilitate recycling and disposal. It is therefore reasonable to assume that the household’s decision to engage in waste minimisation will be determined by the same factors that influence its decision to engage in recycling activities. However, since the amount or level of effort of waste segregation done by the household is also not observable, the study adopted a dichotomous or binary choice model.

716 2.3.

R. Afroz et al. Econometric model of waste generation of the households

To determine the factors that affect waste generation of the households selected, this study followed a multiple regression model. In this regression analysis, the total solid waste generation of the households per month is regressed due to its quantitative nature by several independent variables. The model is: Y ¼ b1 þ b2 X2 þ b3 X3 þ :::::::::::::: þ bk Xk þ e Y ¼ b1 þ b2 Gender þ b3 householdsize þ b4 Age1 þ b5 Age2 þ b6 income1 þ b7 Income2 þ b8 EnvConcern þ b9 willingtoseparate þ b10 Extraland


where: Y ¼ total waste generation by the households per month Xk ¼independent variables b1 ¼ constant term bi ¼ coefficient of independent variables e ¼ the error or disturbance term. In this model the household is viewed as a production unit producing solid wastes. Hypotheses about the nature of the waste production relationship can be stated as hypotheses about coefficient signs of the variables included in the model. Gender was entered as a dummy (Male) that was assigned a value of 1 for males and 0 otherwise. Household size refers to the number of family members living in the same household. Monthly income was measured by two dummies: lower income (Income 1) representing the TK 3000 group and middle income (Income 2) representing the TK3000 to TK15,000 group; the high income (4TK15,000) category was omitted. Multicollinearity between income and education forced us to drop the latter from the estimated equation. Keeping income (rather than education) yielded a better log likelihood ratio and McFadden R2 statistics. Age was entered as two dummies: Age1 and Age2 representing the 16 to 24 and 25 to 35 age categories, respectively; the above 35 age group was omitted. Concern for the environment was a dummy (Environ cons) assigned a value of 1 if the individual was concerned and 0 otherwise. Extra land within the compound was assigned a value of 1 if the household had extra land within their compound and 0 otherwise. Willingness to separate the waste was assigned a value of 1 if the individual was willing to separate the waste and 0 otherwise. 2.4.

Econometric model of willingness to minimise solid waste

The study examines household solid waste minimisation behaviour using binary choice modelling (logit model) following the studies discussed above. The Maximum Likelihood (ML) method was employed to estimate the parameters in logistic regression model. The likelihood ratio index has been measured as an indicator of goodness of fit for the logistic regression model. As such, the model assesses the relationship between various factors and the respondents’ willingness for minimisation of solid waste. The dependent variable is designed as a dichotomous dummy because of assuming whether the household is willing for the minimisation of solid waste or not.


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The data collected via the survey were used to run a logit regression model of the form: Log½P=ð1 PÞ ¼ b1 þ b2 X2 þ b3 X3 þ :::::::::::::: þ bk Xk þ e Log½P=ð1 PÞ ¼ b1 þ b2 Gender þ b3 Age1 þ b4 Age2 þ b5 Income1 þ b6 Income2 þ b7 EnvConcern þ b8 storage


where: Pi ¼ 1 if the household is willing to minimise solid waste Pi ¼ 0 for otherwise Xi ¼independent variables b1 ¼ constant term bi ¼ coefficient of independent variables e ¼ the error or disturbance term i ¼ 1, 2, 3, . . . n Therefore, in this study p/(1 7 p) may be interpreted as the ratio of the probability that the respondent will minimise the waste to the probability that he/she will not. Alternatively, it is the odds of the respondent participating in waste minimisation. Gender was entered as a dummy (Male) that was assigned a value of 1 for males and 0 otherwise. Monthly income was measured by two dummies: lower income (Income 1) representing the TK3000 group and middle income (Income 2) representing the TK3000 to TK15,000 group; the high income (4TK15,000) category was omitted. Multicollinearity between income and education forced us to drop the latter from the estimated equation. Keeping income (rather than education) yielded a better log likelihood ratio and McFadden R2 statistics. Age was entered as two dummies: Age1 and Age2 representing the 16 to 24 and 25 to 35 age categories, respectively; the above 35 age group was omitted. Concern for the environment was a dummy (Environ cons) assigned a value of 1 if the household was concerned and 0 otherwise. The storage facility was a dummy (storage) assigned a value of 1 if the household had a storage facility in house and 0 otherwise. Most of the variables are derived from the interviews, in which it is considered relevant from theoretical point of view and included as independent variables. 2.5.

Survey design and sampling method

Dhaka was chosen as the location for this study. Residents in Dhaka are the immediate beneficiaries of door-to-door waste collection systems that have been introduced by Dhaka city corporation (DCC). The unit of analysis is household – either in an independent house, an apartment, a flat or a shanty and a residence-cum office/business. Those staying in barracks or orphanages and homeless individuals were excluded from the target population as they do not form a household for tax purposes. The reason for choosing ‘household’ as the unit of analysis is linked to the cultural practice in Bangladesh. In most cases a joint-family structure still exists and incomes are combined for the purpose of any expenditure decision. Hence, ‘income’ in this study refers to household income.


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Dhaka comprises 10 zones and within these zones there are 90 wards (subdivision) (BBS 2001). Each ward is composed of one or more mohallas (blocks), each of which contains one or a few streets and a varying number of households. In total, there are 659 mohallas and the number of households in Dhaka city is 643,016 (BBS 1995). This project utilises a stratification process and random sampling on the number of households. First, from each zone we selected one ward with the highest level of waste generation. Two mohallas from each ward were then chosen. This resulted in a total of 20 mohallas from the 10 wards. Next, from these 20 mohallas 413 households were randomly selected in proportion to each zone’s population. Face-to-face interviews were employed in this study because in Bangladesh the literacy rate is low (47.9%) (CIA 2010). After censoring for missing information and inconsistent answers, 402 (97%) were valid for further investigation. According to Sekaran (2003), sample sizes larger than 30 and less than 500 are appropriate for most research. Leedy and Ormrod (2005) also believed that a sample size of 400 is adequate if the target population size is beyond 5000. All the respondents were older than 17 years of age. Before the final data were collected, two pre-tests were conducted in April 2006. The first pre-test involved 10 participants, to test their understanding and clarity of the questions. One week later, 50 individuals were interviewed based on the modified questions from the first pre-test. In August 2006 the final data were collected in Dhaka city. The questions in each interview had three sections. In Section A respondents were asked who normally collected and placed solid waste generated in their households, how many containers of waste each household produced in 3 to 4 days, weight of each container, whether they received a door-to-door collection service and what happened if they failed to get the door-to-door collection, and their knowledge and concern about the environment. ‘Knowledge’ here refers to a respondent’s awareness of waste minimisation and recycling issues, information on what are recyclable and non-recyclable wastes, who can collect wastes and where solid waste can be disposed of (as advertised by Bangladesh Government in the mass media). It should be noted that the government of Bangladesh frequently advertises to explain waste minimisation on television, radio and in newspapers. Among other aspects, the messages in these advertisements include: what is waste, how individuals can recycle, recyclable and non-recyclable items, benefits of waste minimisation and the impact of minimisation of waste. A respondent’s concern for the environment was evaluated based on responses to a set of five questions in the questionnaire. The respondent was only classified as being environmentally conscious if, in response to these questions, he/she satisfied all of the following criteria: perceived a clean environment as a personal responsibility, not the responsibility of other parties; participated in any clean environment campaign or project; disposed of waste responsibly during outings when no waste bins were available; was involved in some environmental protection activity; and rated him/herself as being environmentally conscious. Section B asked the respondents about their sources of knowledge, recycling activity, waste disposal practices and whether they were willing to minimise their household waste. Here, waste minimisation refers to separating the solid waste from recyclable materials, composting organic materials, giving the solid waste to waste collectors and selling the recyclable materials. Next respondents were asked how often they recycled their solid waste. Section C covered socio-economic characteristics (education level, employment, household monthly income, age and number of


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family members) and miscellaneous issues (extra land and any other comments that respondents wished to express).


3.

Results

3.1. Socio-economic characteristics of the respondents Tables 1 and 2 show the socio-economic characteristics of the respondents. Table 1 shows the gender, religion, education and employment characteristics. The study found that 67.1% of the respondents were male and 32.9% female. Dhaka’s population growth is at 56.5% (2001 Census) (BBS 2001) and the gender ratio is 1.26 male to 1 female (Hassan 2008). In this survey, 80.2% of the respondents followed Islam, 16.4% were Hindu, 3.0% were Christians and 0.4% were Buddhists. A total of 83% of Bangladeshis (CIA 2010) are Muslim and Islam is the dominant religion in Dhaka city. The highest percentage of the respondents had a university degree (61%) followed by diploma (13.4%), higher secondary certificate (11.8%), secondary school certificate (5.7%), primary level (4.8%) and 3.3% had no formal education. Most of the respondents appeared to have tertiary education. A total of 47.9% of Bangladesh’s population are literate, and the figure is 62.3% in Dhaka (Wikipedia). The proportion of respondents with a university degree was quite high for a developing country like Bangladesh. It could be that many of those who have a tertiary education decide to reside in Dhaka city. Most of the respondents (53.7%) were service providers (in paid employment), 22.4% were businessmen, 19.5% were housewives and 4.4% were retired. The unemployment rate in Bangladesh is 2.5%, with the workforce in agriculture (45%), industry (30%) and services (25%). While unemployment in Dhaka remains high at 23%, half the workforce is employed in household and unorganised labour, while approximately 800,000 work in the textile industry (Wikipedia 2010). Table 1.

Gender, religion, education and employment of respondents.

Item Gender Male Female Religion Islam Hindu Christian Buddhist Education No formal education Primary education Secondary school certificate (SSC) Higher school certificate (HSC) Diploma University Employment Service holder Business man Housewife Retired

Number of respondents (N ¼ 402)

Percentage

270 132

67.1 32.9

322 66 12 2

80.2 16.4 3.0 0.4

13 19 23 47 54 246

3.3 4.8 5.7 11.8 13.4 61.0

216 90 78 18

53.7 22.4 19.5 4.4

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Table 2. Respondents’ household income, age, number of family members and extra land available. Item


Household monthly income Age in years Family members (number of persons) Extra land with the compound

Number of respondents

Average

Taka (US$) 402 402 402

120,00 (176.1) 39 4 0.5 acres

Table 2 shows the respondents’ socio-economic background in terms of household income, age, number of family members and extra land in the compound. On average the monthly household income of the respondents was US$176.1 (US$1 ¼ 70.1BD Taka). Despite many having tertiary education, the respondents earned far less than the target population. It was reported that Bangladesh’s GDP per capita (purchasing power parity) is $1600 (CIA 2010) per month while the annual per capita income of Dhaka is estimated at $ 500, with 48% of households living below the poverty line, including a large segment of the population coming from the villages in search of employment, with many surviving on less than $10 a day (Wikipedia 2010). Based on the amount of household income, the respondents were divided into three groups: below TK3000 (lower group), TK3000 to TK15,000 (middle group) and above TK15,000 (higher group). A total of 56% of the households were from the higher group, 23% from the middle group and 11% from the lower group. Contrary to this division, Dhaka city has a growing middle-class population (Wikipedia 2010). The average age was just under 39, with the lowest being 32 and the highest 65 years old. The average household size was four, the maximum ten and minimum two. The average size of extra land in the compound was 0.5 acres. 3.2. Waste generation in the households The respondents were asked who normally collected and placed solid waste generated in the households. Servants/maids were in charge of waste disposal for 89% of the higher-income group and 79% of the middle-income group, while members of the households, mostly wives and daughters, were in charge among 94% of the lowerincome group. Attitudes towards waste disposal (as a menial task) or the social status of such a job imply that even within a household this task is likely to be done by the weaker members, for example, children or dependent women such as a widow or a daughter-inlaw or house maid. The respondents were asked how many containers of waste each household produced every three to four days. Most respondents (56.4%) produced three to four waste containers (Figure 1). A typical waste container contained around 1 kg of waste. Waste generation in the study area averaged 38kg/month for each household. As the household average number is four, the waste generation averaged is 0.3kg/day per capita, which is similar to the findings of DCC (2005). A door-to-door collection service was received by 82% of the upper-income group households, 75% of the middle-income group and 30% of the lower-income group. This shows that the door-to-door collection services are not consistent for all households and those belonging to the upper-income group of households are more fortunate. Failing to get the door-to-door collection services, 51% of the lower-income group of households dumped their waste in vacant lands/river/marshes, while 5% of the upper-income group and 4% of middle-income groups behaved in a similar manner.



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Figure 1. Packages of waste in 3–4 days (n ¼ 402). Note: 1 package ¼ 11 inches x 15 inches plastic shopping bag, contained about 1 kg of waste.

Figure 2.

Sources of knowledge about recycling (n ¼ 402).

3.3. Knowledge about solid waste minimisation The respondents were asked about their knowledge of solid waste minimisation. A majority of the respondents (61.94%) stated that they had knowledge about solid waste minimisation. Figure 2 shows that the majority obtained their source of knowledge from newspapers (50.2%), television (20.9%) and radio (4%). In this case, newspapers and television have been most influential in promoting environmental issues. 3.4. Waste recycling practices With regard to solid waste minimisation, the respondents were asked how often they recycled their solid waste. Concerning recycling practices, only 25.6% regularly recycled (Table 3), 18.2% seldom recycled and 56.2% never recycled. It should be noted that most people in Dhaka have not been, and still are not, served by any

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convenient recycling network. The high figure for those who seldom or never recycle (74.4%) agrees with the study conducted by DCC, showing a high level of solid waste in Dhaka city. Of those who regularly recycled (25.6%), a majority separated recyclable materials from solid waste and sold it (74.4%), followed by those who separated the waste and gave it to waste collectors (20.9%) and those who separated the waste, sold recyclable materials and composted the organic materials (4.7%) (Table 4). The reasons given (Table 4) by those who practised waste separation at the source were: good for the environment (68.0%), earn extra income (21.4%) and allows for waste composting (10.7%). Table 5 shows why respondents seldom or never recycled their wastes (74.4%), reasons given were: lack of time (38.49%), no space at home (37.2%), recycling is expensive (12.0%), no economic incentives (3.9%), no recycling facilities (3.09%) and no reason (5.4%). This group of households (seldom or never undertake recycling) were also presented with another

Table 3.

Practice of recycling.

Answer


Percentage

226 73 103 402

56.2 18.2 25.6 100

Never practised recycling Seldom did Regularly practised it Total

Table 4.

Respondents who regularly recycle. Number of respondents (N ¼ 103)

Percentage

77

74.4

22

20.9

4

4.7

70 11 22

68.0 10.7 21.4

Method of recycling Separate the recyclable materials from the waste and sell them Separate the waste and give them to waste collectors Separate the waste, sell the recyclable materials and compost the organic materials Reasons for regularly recycling Good for environment Allows for composting Earn for extra income

Table 5.

Reasons for seldom or never recycling.

Reasons There was no facility for recycling Lack of time No economic incentive No space at home No reason Expensive to recycle Total


Percentage

9 115 12 111 16 36 226

3.1 38.5 3.9 37.2 5.4 12.0 100


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scenario in which the government provided them with a container to keep and separate their household waste. Interestingly, 30.1% of the respondents were willing to minimise their waste if facilities were provided. 3.5. Perception and attitude of the respondents about solid waste management Table 6 shows the questions related to the perception, willingness to pay and attitudes of the households. Questions 1 to 4 concerned their perception; questions 5 to 7 concerned the households’ willingness to pay; and questions 8 to 10 concerned the attitudes of the households. All data collected were then analysed using statistical tools for simple percentages, frequency analysis and severity index calculations. The answers to questions were displayed on a 0 to 4 point Likert Scale, while the severity index (SI) was calculated using the following equation developed by Al-Hammed and Assaff (1966): P4 i ai x i SI ¼ P ð100; %Þ; 4 4i xi where: ai ¼ the index of a class; constant expressing the weight given to the class xi ¼ the frequency of response i ¼ 0, 1, 2, 3, 4 and described as below, where X0, X1, X3, X4 are the frequencies of response corresponding to a0, ¼ 0, a1, ¼ 1, a3, ¼ 3 and a4 ¼ 4 respectively. The rating classification was adapted developed by Majid and McCaffer (1997). a0 a1 a2 a3 a4

¼ ¼ ¼ ¼ ¼

strongly disagree 0.00 SI 12.5 disagree 12.5 SI 37.5 neutral 37.5 SI 62.5 agree 62.5 SI 87.5 strongly agree 87.5 SI 100

On the point scale, the ratings given to the households are as follows: strongly disagree (0), disagree (1), neutral (2), agree (3), and strongly agree (4). For the ease of interpretation, each rating is given the following denotation: Strongly disagree (SD) Disagree (D) Neutral (N) Agree (A) Strongly Agree (SA) Only the responses to the questionnaires directly related to the scope of the present study have been analysed and discussed. The results of the assessment of the general perception, willingness to pay and attitudes of households to waste management are presented in Table 6. Table 6 presents calculated values of severity indices related to the perception of the households about waste management. The values ranged between 46.9% and 60.1%. The values are found within the neutral opinion range of 37.5 SI 62.5 (Majid and McCaffer 1997, Isa et al. 2005). With this opinion range the households affirm the existence of an organised solid waste

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Table 6. Perception, willingness to pay and attitude of the respondents about solid waste management. Frequency


Questions 1. There is an organised waste disposal programme in my area 2. I am satisfied with the services of the service provider in my area 3. Separate plastic bags for waste collection should be provided by the waste collector 4. Waste management improvement is not important 5. I am ready to pay for the disposal of waste I generate 6. I am not ready to pay for the disposal of waste I generate 7. Earning more income will encourage payment for waste disposal services 8. I am willing to implement and participate in a waste management programme 9. Practise waste segregation regularly 10. Encourage community to practise waste management at source

SD(0)

D(1)

N(2)

A(3)

SA(4)

NR PR

NR PR

NR PR

NR PR

NR PR

28

7

57 14.2 124 30.8 165 42

7

56.7

57 14

46.9

61 15.2 133 33.2

59 14.8

57 14.3

43 10.6

49 12.1 192 47.8

62 15.2

60.1

101 25.3

90 22.4

18

4.5

96 24

97 23.8

54.9

77 19.2

91 22.7

23

5.9

92 22.8 118 29.4

55.0

5

1.2

5

1.2

9

82 20.3

62 15.3

49 12.1

92 23

28

(SI)%

2.3 154 38.3 229 57

87.1

36

9

90 22.5 132 32.9

57.9

53 13.2

28

7

94 23.6 177 44.1

68.3

116 29.1

84 21.0

13

3.2 129 32.2

58 14.5

45.3

72 17.9

81 20.2

20

4.9 125 31.2 104 25.8

56.7

management system in Dhaka. The survey results indicate that the rate of willingness to pay is relatively high across the study area. The values are found within the agreed opinion range of 62.5 SI 87.5 (Majid and McCaffer 1997, Isa et al. 2005). The study has also found that the values of severity index related to the attitude of the households ranged between 45.3% and 68.3%. The values are found within the


725

neutral opinion range of 37.5 SI 62.5 (Majid and McCaffer 1997, Isa et al. 2005). The values indicate that the households are willing to implement and participate in a waste management programme and encourage the community to practice waste management at source.


3.6.

Estimation results of waste generation and the socio-economic model

All estimation analysis used in this study was undertaken by using the econometric package Limdep Nlogit 8.0 (Greene 2006). The estimation result of waste generation and the socio-economic model is shown in Table 7. It is evident that environmental consciousness and the middle-income group (Income 2) are significant positive predictors of waste generation (at the 1% level). Another variable, willing to separate, is also positively correlated with waste generation (at the 5% level). As might be expected, the coefficient for the attitudinal variable for concern about the environment is positive and statistically significant, which supports the hypothesis that the respondents who are more concerned about the environment in Dhaka would have generated less waste and be willing to have an improved solid waste management programme. The positive coefficient on the middle-income group (Income 2) variable indicates that holding all other variables constant, middle-income earners are generating more waste than those in the lower and higher-income groups. The positive relationship between these two variables is generally supported by the previous literature (Hong et al. 1993, Jenkins 1993). The positive sign for concern about the environment is supported by the results of the study conducted by Jin et al. (2006). The positive coefficient for willingness to separate wastes means that the respondents who agree to separate waste at their house are willing to recycle more and generate less waste. Overall, the model depicts a satisfactory goodness of fit with the McFadden R2 value of 0.36. The goodness of fit of the model is evaluated using the McFadden R2 or the likelihood-ratio (LR) index, which compares the likelihood for the intercept only model to the likelihood for the model with the predictors. The value of the LR statistic (p 5 0.00001)

Table 7.

Factors affecting waste generation. Variables

Estimation

Standard error

t-statistics

Constant Male 16–24 years (Age1) 25–35 years (Age2) House size Lower income (Income1) Middle income (Income2) Household size Willing to separate the waste Extra land Environmental conscious LR statistics McFadden R2 Probability Total number

70.12 70.12 70.11 0.11 0.31 0.04 0.76 0.45 0.56 0.08 0.52 7121.24 0.36 0.00000 402

0.32 0.20 0.09 0.15 0.20 0.21 0.12 0.36 0.12 1.58 0.13

70.37 70.6 71.22 0.73 1.55 0.19 6.33*** 1.25 2.33* 0.05 4.00***

*Significant at p 0.05; ***Significant at p 0.01.

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R. Afroz et al.


shows that all the variables have a significant effect on the waste generation of the households. 3.7. Estimation results of willingness to minimise solid waste and the socio-economic model Table 8 shows the estimation results of willingness to minimise solid waste and the socio-economic model. It is evident that environmental consciousness is a significant positive predictor of waste minimisation (at the 1% level). The middle-income group (Income 2) is also positively correlated with waste minimisation (at the 5% level). Another two variables, age (25–35 years) and storage, are also significant (at the 5% level) but age has a negative relationship with waste minimisation. The results in Table 8 confirm that environmentally conscious individuals are more likely to minimise waste, although this is not consistent with some studies (Knussen et al. 2004, Oom et al. 2005, Carrus et al. 2008). According to Mohai (1985), decisions and attitudes towards the environmental protection effort depend on degrees of personal efficacy and resource availability. With regard to the predictive effect of family income on participation in environmental development programmes, several studies have shown that households with higher income levels are more propitious to engage in environmental development programmes (Jacobs et al. 1984, McGuire 1984, Vining and Ebreo 1992, Berger 1997, Owens et al. 2000). Similarly, the present study also shows a positive relationship between income and willingness to minimise solid waste. More interestingly, the middle-age group of respondents (25–35 years) is significantly more likely to be willing to minimise waste than those in the youngest and oldest age groups. These results may be interpreted as follows: the youngest respondents have not yet accepted the need to minimise waste, while the oldest respondents belong to a generation that never saw the need to minimise waste. Waste minimisation and concern for the environment is a relatively recent phenomenon; in time, it is likely that the positive correlation between the likelihood of waste minimisation and age will become more apparent in Dhaka, Bangladesh. Demographic variables such as gender and age have not

Table 8.

Factors affecting willingness to minimise solid waste.

Variables

Estimation

Standard error

t-statistics

Constant Male 16–24 years (Age1) 25–35 years (Age2) Lower income (Income1) Middle income (Income2) Storage Environmental conscious LR statistics McFadden R2 Probability Total number

71.12 70.28 70.03 0.54 0.02 0.54 0.92 0.52 7112.3 0.41 0.00000 402

0.32 0.20 0.14 0.21 0.41 0.26 0.45 0.13

73.5 71.41 70.21 2.57* 0.04 2.07* 2.04* 4.56***

*Significant at p 0.05; ***Significant at p 0.01.


727


shown consistently significant correlation with recycling behaviour. Studies in the Netherlands, Germany and Norway suggest that older respondents are more dedicated to recycling (cited in Fenech 2002, Martin et al. 2006). It was hypothesized that this concern reflected the frugality of the older generation. Several authors (Jenkins et al. 2000, Barr et al. 2001, Guerin et al. 2001, Barr and Gilg 2005) have reported similar findings. Blaine et al. (2001) and Fenech (2002), on the other hand, suggest that older people recycle simply because they have more time on their hands, indeed, recycling is a time-intensive activity (Bruvoll et al. 2002, Martin et al. 2006). Overall, the model depicts a satisfactory goodness of fit with a McFadden R2 value of 0.41. The value of the LR statistic (p 5 0.00001) shows that all the variables have a significant effect on the waste minimisation of households. 4.

Conclusion and policy implications

The willingness to minimise household waste is an important component for the sustainable development of waste minimisation projects in Bangladesh. As the residents of Dhaka city are the main group of contributors to the waste minimisation programme, the success of this programme depends on their willingness to implement it. This study investigated factors that affect waste generation and respondents’ willingness to minimise solid waste. Important determinants of the waste generation are environmental consciousness, the middle-income group (TK3000 up to TK15,000) and willingness to separate. Environmental consciousness, the middle-income group (TK 3000 up to TK15,000), young adults (25 to 35 years old) and storage facilities are the most important factors for respondents’ willingness to minimise solid waste in Dhaka city. In recent years reducing and recycling household waste has become increasingly imperative because waste generation has been increasing due to population growth and economic development, and resources are becoming scarce, making recycling not only a sensible practice but essential. Although there is widespread public support for reducing and recycling household waste, this is not reflected in participation levels in Bangladesh. With regard to issues about the reduction of solid waste, the findings of this study are helpful to environmental and waste minimisation planners as well as to policy makers. First, this study found that there are important indicators of positive attitudes of residents toward solid waste minimisation. For example, 30.1% of the households in the study were willing to minimise their household waste. The study also found that only 25.6% of the households were recycling regularly. Using the severity index analysis, it was found that the households agreed to implement and participate in the waste management improvement programme. Now, the question is if they agree to separate their waste and agree to implement and participate in the waste management programme, why is there low participation in waste minimisation? The study suggests that we should investigate what discourages them from participating. In order for the waste minimisation programme to be successful, the behaviour of the households in Dhaka city toward solid waste minimisation should be taken into consideration. Second, another way to reduce solid waste is by encouraging the residents of Dhaka to recycle and separate their waste at source, as is done in many developed countries. It is evident that concerted efforts to raise environmental consciousness


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through education and more publicity regarding waste separating, reducing and recycling could affect households’ waste generation. Third, a door-to-door waste collection service is not available to all households in Dhaka. The DCC should monitor this service, observe the satisfaction of the households with the service and ensure all households receive the same treatment from the solid waste collectors. For example, in their study Afroz et al. 2009 found that 54.6% of the households in door-to-door waste collection receiving areas were not satisfied with the waste collectors in Dhaka. They suggested that waste collectors could motivate the households to minimise their solid waste. Fourth, findings in this study show that households who are environmentally conscious are more willing to minimise their waste. As such, policies should be formulated to focus on raising awareness, promoting knowledge and motivating households with regard to the environment, waste generation and waste minimisation practices. Fifth, since in Dhaka the recycling centres are not near to the households and the dustbins are also some distance away, the DCC should look into this matter carefully. Sixth, findings in this study show that middle-aged people are more willing to minimise waste than those who are young or old. Old people are more resistant to new ideas because they do not want to change their beliefs and lifestyle. However, young people could be encouraged at school or college by introducing topics on different environmental problems, including waste management, in their syllabus. If they learn about it at school or college, it would be easy for them to adopt waste minimisation practices in later life. On the other hand, parents can also play their role in waste minimisation. Setthasakko (2009) conducted a qualitative approach research in Thailand, and the findings showed that the culture about waste management, especially recycling, should be taught to children from a very young age. Parents must be committed to implement a waste management system in their household, and if this system is not followed by the whole family the parents can form a penalty that relates to environmentally-friendly activities such as cleaning a drain, mowing the lawn or planting flowers. Finally, recycling should be encouraged by legal and business policy mandates, as well as by increasing taxes on virgin resources (Tiemstra 2002). In this project, compliance suffers when individual households cannot be held accountable for their behaviour (Gandy 1993). 5. Limitations of the study and future research There are a few limitations to this study. First, the sample in the study is not representative of Dhaka as a whole, thus the findings cannot be generalised. The findings are applicable and limited to the area under investigation. Second, the population sample for those who practice recycling regularly is low (103 respondents, 25.6%), thus the findings should be used with caution. Third, the number of respondents who had extra land was extremely limited so the researcher was unable to analyse this perspective. Therefore, future researchers should consider all these limitations when they plan their research relating to solid waste management. Conducting research specifically targeting those in the sample who participate in solid waste management might give a different outcome to the study. Moreover, researching a target sample who have extra land in their compound might show another view of solid waste management.


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