Anatomizing the Dynamics of Societal Behaviour towards E-waste Management and Recycling Initiatives: A Case Study of Kolkata,India

Abstract

It is a truth universally acknowledged that waste is continually generated in the course of production and consumption of products and materials. While augmented recycling and recovery initiatives are being undertaken to combat the ecological impact of skyrocketing municipal waste volumes, individuals must also be parallelly responsive towards the overwhelming environmental concerns sparked by the rapidly increasing volumes of electronic waste (e-waste) in the opted city of Kolkata, India. E-waste is a hazardous concoction of heavy metals such as lead, cadmium, mercury, barium or arsenic, in addition to other halogenated compounds; its unconscionable disposal can adversely trigger soil and groundwater pollution, while taking its toll on human health as well as multifarious flora and fauna. In an attempt to remedy the problem in hand, the present study purports to investigate the attitudes, knowledge and behaviour of Kolkata’s populace, in light of e-waste management and recycling behaviour. With the aid of a structured questionnaire, an aggregate of 242 respondents have been surveyed, so as to gain cognizance of their voices and concerns towards e-waste management. The results have been scrutinized in order to prescribe diagnostic explications to policy-makers and general masses alike, such that appropriate measures may be undertaken to endorse recycling behaviour across all Indian households.

Keywords

E-waste management attitudes recycling behaviour awareness environment

Background Reflections

The skyrocketing degrees of industrial pollution, coupled with the inordinate increase in consumption levels across major nations of the world, has questioned the successful attainment of sustainable development, thereby making it imperative to conserve existing resources and maintain regimented levels of waste materials. According to a report published by the Central Pollution Control Board in 2014, Kolkata generates around 1.1 million tonnes of municipal solid waste (MSW) annually, which is around one-third of Delhi’s solid waste generation. Truth be told, the landfills of most of these cities are already brimming, with no space to accommodate fresh garbage. According to Roychowdhury (2014), the primary reason why most landfill sites are overflowing is because the current waste disposal system is flawed. In accordance with the study conducted by the South Asian Forum for Environment in 2013, approximately 5,372 tonnes of solid waste was collected in Kolkata, with a daily average of 1.4 kg of MSW per individual per day; alarmingly only 37 per cent of this aggregate MSW generated daily is compostable. While a mere one-third of the MSW generated is organic matter, nearly a fifth of the waste comprises recyclable materials. The situation is so disquieting that a novel 30-acre landfill site at Action Area III of Rajarhat-New Town region, in close proximity to the Kolkata International Airport, has been sanctioned by West Bengal Housing Infrastructure Development Corporation on the likes of the South Korean waste disposal model, simply because the existing vast landfill site at the Dhapa wetlands was inept in handling existing waste volumes of the city.

Needless to mention, the pivotal reason for the rapid upsurge in environmental pollution as well as spiralling of waste volumes across cities, is the density of industrial establishments and populations across multiple regions coupled with the extreme proliferation in consumption and consumeristic trajectories over the past decade. Rapid advances in technology have largely accentuated consumption trends, which have spawned new types of waste materials. As the Indian petite bourgeoisie expands, consumption patterns bear testimony to the fact that consumers are increasingly becoming more and more impatient and are resorting to profligate use of finite resources so as to mirror their ostensible ‘fast-paced upscale living standards’. Contemporary studies in garbology reflect valued information on the nature and metamorphosing patterns in modern refuse, and thereby, consumer behaviour and human society. Various inquests have been made into the waste categorizations across the country, in order to gain a holistic understanding of the disposal rates of various incipient natures of waste. As the consumer durables and electronic appliances sector sprouts throughout India, the proportion of electronic wastes in garbage is swelling dramatically as well. The revolution in the domain of information and telecommunication technology has profoundly affected the world in myriad dimensions. The undemanding availability and utility of smarter and faster machines marked by the brisk pace of technological breakthroughs has radically transformed our lifestyles and has been the raison d’être for the increasing rates of consumption and dissipation. This high consumption pattern of technology-centric living has led to the emergence of the new waste stream of electronic waste (e-waste), which encompasses a host of metals such as copper, aluminium and gold and are known to release hazardous metals such as lead, cadmium and mercury when they are reassembled, dismantled, burned or processed chemically for recycling or reuse purposes (Kaya & Turan, 2005). The toxic nature of this waste, due to the presence of materials such as lead, cadmium and mercury makes it a critical issue to be dealt with.

Introductory Contemplations

Backed by perennial ameliorations and upgradations in technology, the electronic industry continues to be the world’s largest and fastest growing manufacturing segment; all developments in this domain have momentously empowered consumers, especially over the past couple of decades. In fact, the awareness of this fact has nurtured the desire for consumers to adopt the hottest technologies regardless of their ecological repercussions. Present studies report that the Indian middle class is expected to tap 583 million by 2025, enabling India to become the fifth largest consumer market across the globe. In Kolkata, as with the rest of the metros in India, there has been a remarkable ascent in electrical and electronic equipment (EEE) consumption over the past few years. With increasing prosperity and revolutionizing standards of living, individuals and groups have sought more convenient ways of doing things. As the global market for EEE continues to escalate exponentially along with the consistent advent of pioneering designs and smart technology, a correlated concern of rapid obsolescence of multiple electronic items has cropped up over the past few years. This desuetude has prompted waning life cycles of several electronic products, thereby sparking mounting disposal rates. For instance, according to a study by Denga (2006), the average life of computers and mobile phones have been dragooned to below two years, steered by the continual advancements in alluring consumer designs, marketing strategies and compatibility issues.

Corporate and waste management officials as well as policy-makers are thus exposed to the new-fangled challenge of managing soaring e-waste volumes across major cities and regions of the country, given that its prolonged mismanagement has been triggering problems of contamination and pollution all across the globe. The Environmental Protection Agency defines electronic waste as electronic products that are discarded by consumers; in fact, this definition engulfs almost all types of EEE that has or could enter the waste stream. The improper disposal of these products adversely affects human and environmental health, as many of these products comprise toxic substances. Kurian (2007) has observed that e-waste that includes iron, aluminium, gold and other metals comprise over 60 per cent of these products, while plastics account for about 30 per cent and hazardous pollutants comprise 2.7 per cent. According to a study by Sushant, Wath, Dutt and Chakrabarti (2011), the primary materials found in e-waste are ferrous substances (38 per cent), nonferrous substances (28 per cent), plastic (19 per cent), glass (4 per cent) and others, including wood, rubber, ceramics and a host of other materials (11 per cent). It is quite evident that e-waste is a direct consequence of soaring rates of obsolescence and the ‘throw-away’ mentality of today’s consumers. In fact, an earlier rudimentary study conducted by the Centre for Quality Management System at Jadavpur University, Kolkata (2005) revealed that approximately 800 computers were becoming obsolete in India on a daily basis. The irony lies in the fact that the disposal attitude of consumers translate into the escalating sales of electronic equipment, thus casting no impact on corporate profits, given that the electronics industry is not necessitated to bear any financial burden of downstream costs. The principal area of concern is the efficient management of e-waste, which lies among the top-most agendas for curbing pollution problems across India. Novel technologies are fast superseding heaps of analogue appliances, leading to their disposal in prescribed landfills despite their potentially adverse impacts on the environment. E-waste is generated largely by three major sectors in India, namely

Individuals and small business units

Large business establishments, government and financial institutions

Original equipment manufacturers (OEMs)

Vardhan (2015) in his study has observed that India generates 0.13 million tonnes of e-waste annually, which is increasing at a startling annual rate of 26 per cent. Interestingly, the city of Kolkata is the major centre of e-waste in eastern India. Estimates of annual e-waste generated in the city have fuelled up from around 9,000 tonnes to 26,000 tonnes in a span of mere three years. Most of the e-waste ends up in the informal sector leading to environmental hazards, and their processing and recycling centres are spread across various localities, thereby making it rather arduous to precisely quantify the e-waste volumes in the city. Pillared on the data furnished by WEEE Recycle (2015) on their website, the major ‘hotspots’ of e-waste may be identified as Chandni Chowk, Phool Bagan, Princep Street, Maniktala, Kankurganchi and Kadapara. Suburbs of the city, which embrace Howrah, Hooghly, Salt Lake, Kalyani, Barasat and Uluberia, are also reported to house recycling centres. With the city becoming a major IT and (planned) financial hub, the magnitude of the e-waste is only expected to rise in the future. Further, there are several reports and indications which suggest that the city not only generates waste of its own but also receives waste from the adjoining states. By the end of the next decade the potential e-waste in the city is expected to touch 0.02 million tonnes annually. Given such a possibility, earnest and well-coordinated initiatives are mandated for effective management of e-waste in the years to come. The challenge is only snowballing with the persistent invention of avant-garde electronic gadgets, increasing disposable income, and changing urban lifestyles.

Review of Associated Literature

It is a well-established fact that waste is an offspring of economic growth and development. The IT industry growth coupled with the augmentation in consumers’ preferences for sophisticated equipment and gadgets has added another dimension to the existing conundrum of titanic MSW volumes in Kolkata. E-waste is now a reality in this largest city of eastern India. Waste from electrical and electronic equipment (WEEE) is considered to be a critical waste stream owing to its potentially hazardous nature, irrational consumption of resources and expected growth rates.

Before we proceed further, we need to clarify certain concepts in light of former researches on the said domain. The elucidation of these terminologies based on existing literature, shall pave the way for further research and a clearer understanding of our research problem. Puckett et al. (2002) define e-waste as a broad and flourishing array of electronic devices ranging from large household devices such as refrigerators, air conditions, cell phones, personal stereos and consumer electronics to computers that have been discarded by their users.

Again, Sinha-Khetriwal (2002) has classified e-waste as any electrical powered appliance that has reached its end-of-life. In point of fact, there exists no clear definition of the term e-waste. We shall thus define e-waste as the refuse in the aftermath of decline of an EEE, when a new-fangled technology effaces the inherent need of the preceding product, be it a laptop, smartphone or plasma television.

Robinson (2009) focused on the technical constituents of WEEE and threw valued light on the possible upshots on the immediate environment, from a long-run perspective. It was noted that television and computer monitors generally contain hazardous substances such as lead, mercury and cadmium, while nickel, beryllium and zinc can often be traced in circuit boards. The physical composition of e-waste is assorted and encloses over a thousand miscellaneous substances that can be categorized into organic or inorganic fractions. Heavy metals form a significant part of inorganic fraction, accounting for 20–50 per cent. E-waste consists of hazardous metallic elements like lead, cadmium, chromium, mercury, arsenic, selenium and precious metals like silver, gold, copper and platinum. An overview indicates that manufacturing of mobile phones and personal computers consumes 3 per cent of gold and silver mined annually worldwide, as well as 13 per cent of palladium and 15 per cent of cobalt. Both hazardous and valuable heavy metals are non-renewable and are hence envisaged to become precious finite resources in the future. Due to the presence of these substances, recycling and the disposal of e-waste has developed into a major challenge, and its efficient management has become a herculean task due to the various hurdles presented in terms of technical, financial, strategic or information asymmetry. The general consensus is that there is an urgent need for managing e-waste in a formal, systematic and eco-friendly manner by way of recycling precious metals from waste streams.

E-waste is said to be the fastest growing waste stream in the world (Jain, 2008), with a global annual growth rate of 3–5 per cent (Mohan et al., 2008).

The United Nations University (UNEP, 2009) estimated that 20–50 tonnes of e-waste is generated annually worldwide and subsequently prescribed the pressing requisite for the development of an estimation technique in resource conservation and e-waste management.

In fact, an US Environmental Protection Agency Report (USEPA, 2011) analyzed that the growth rate of e-waste is three times swifter than that of general waste, which presents a formidable managerial challenge especially to the developing countries.

After having conceptualized the rudiments of e-waste, we need to focus our attention towards the widespread repercussions cast by WEEE on the individual, societal and ecological levels. Managing e-waste is an exigent task, not only due to its rapidly increasing volumes, more pertinently due to its hazardous nature. In a research embarked upon by Pronczuk (2005), it was discerned that foetuses, children, pregnant women, elderly people, people with disabilities, workers in the informal e-waste recycling sector and other vulnerable populations encounter supplementary exposure risks. It was also noted that children were a predominantly sensitive group, owing to the presence of additional routes of exposure such as breastfeeding, sundry high-risk behaviours such as hand-to-mouth movements in the germane years, high risk-embracing behaviours in the adolescence phase and their changing physiology in terms of greater intakes of air, water and food, and low rates of toxin elimination.

The above study was henceforth enhanced by Grant et al. (2013), where it was pointed out that the children of e-waste recycling workers were also exposed to take-home contamination from their parents’ work-clothes and skin, as well as direct high-level exposure in the event of home-based recycling activities.

Another study executed by Woodell (2008) highlighted that, in contrast to archetypal MSW, certain components of EEEs encompass toxic materials that can generate profound threats to the environment as well as to human health.

According to Herat and Agamuthu (2012), open incineration of e-waste disposal poses a colossal threat to public and environmental health, in terms of heath disorders, increased toxicity in the atmosphere and rampant soil pollution.

Having discussed the potential consequences of e-waste on the societal and ecological framework, we must focus on the Indian scenario. It has been observed that the level of awareness and contemplation on the issue of e-waste is rather minimal across the country. There exists quite a few prescriptive and conceptual articles which merely capture the theoretical dynamics of e-waste, but very few pieces of the literature actually address the real-life and contemporary impact of WEEE on the environment and its executable diagnosis. A few studies, however, have been identified in the Indian context, which addresses the issue of e-waste management from a more practical standpoint. According to a study undertaken by Ghosh and Mahesh (2007), it has been estimated that the city of Kolkata generates most of the e-waste from as computers and its peripherals as well as consumer durables such as televisions, microwave ovens and refrigerators. The amount of waste generated only from computers and its peripherals is assessed to be around one-third of the total composition of e-waste. The quantity is projected to increase exponentially as the city is still going through a surge in computer usage; these machines are expected to arrive at the waste stream post their useful life, which is estimated to be roughly around three to five years. The offices, which generate bulk of this waste, are barely aware of the toxins in these equipments and hence dispose waste indiscriminately. The study undertaken by Toxics Link, New Delhi, in association with Centre for Quality Management, Jadavpur University (2007) also testifies that the users believe in the need for a legal framework for e-waste management with producers taking responsibility of the end-of-life equipment. The study also evidenced that the influx of WEEE is much more than the normal standard, owing to the massive volumes of waste inward bound from the other centres in West Bengal as well as from the neighbouring states. Informal deliberations and interviews have also revealed that waste from foreign countries have been reaching the city through the Kidderpore dock region. The existing scrap dealers in the city have taken up the job of processing and recycling of e-waste and acquire waste through tenders and auctions.

Viraja et al. (2012) observed that in emerging economies like India, existent e-waste management practices are shambolic, which may infuse deleterious impacts on human health and the environment. The authors proposed the conception of an efficient mechanism for resource removal or recovery, such that dear metals could be conserved more effectually.

Although the above papers capture the essence of WEEE and its hazardous influences towards individuals and their immediate environment, only a mere handful of papers concentrate on the issue of consumer awareness towards these perils. It is reflective of the fact that a sizeable proportion of consumers in India may still be in the dark when it comes to e-waste and scientific recycling initiatives to tackle the stumbling block.

Bhutta et al. (2011) commented that most people are still unaware of the potential negative impact of the rapidly increasing use of computers, monitors and televisions. When these products are placed in landfills or incinerated, they pose health risks due to the hazardous materials they contain. The unscientific disposal of electronic products leads to the possibility of environmental degradation. As more e-waste is heaped in landfills, exposure to environmental toxins is likely to swell, resulting in elevated risks of cancer as well as developmental and neurological disorders.

In a study undertaken by Irra (1999) in Malaysia, it was unfurled that only 59 per cent of the households were moderately aware with some elementary knowledge and were mildly alert to solid waste issues; Mamat and Chong (2007), in their study, found that the challenge still remained in transforming the attitudes of consumers towards ethical and systematic recycling of e-waste.

In fact, Saritha, Kumar and Srikanth (2015) have rightly asserted that the volume of WEEE intensifies precipitously every year and is also believed to be one of the most critical waste disposal issues of the twenty-first century. In Kolkata, along with other major cities of India, we are still at a fundamental level, where the focus is on enlightening people on the dynamics of e-waste, its divergence from typical solid wastes and how recycling initiatives must be undertaken at an individual and societal level at the earliest. It is thus evident that there exists a distinct research gap, when it comes to unravelling the intricacies of societal behaviour in India towards the awareness of e-waste and hence maintaining a favourable attitude towards versatile systematic recycling initiatives.

Research Model and Hypothesis Formulation

The present study seeks to probe into the behavioural trajectories of households and individuals with reference to e-waste management in the city of Kolkata. These have been hypothesized as follows:

Awareness Levels of Consumers towards E-waste (CALEW)

It refers to the familiarity with the hazardous nature of e-waste in the cognitive scaffolds of the consumer’s mind. This hypothesis shall seek to unfurl how far consumers are au fait with the ecological and individual repercussions of e-waste disposal in terms of environmental degradation and sufferance of human health. In fact, the ability to identify, recognize or recall the toxic composition of e-waste shall be symbolized as CALEW. We shall hereby analyze the association between said awareness levels and the attitudes borne by customers towards e-waste recycling, which can be hypothesized as:

H1: Awareness levels of consumers towards e-waste has a positive influence on consumer attitudes towards recycling of e-waste.

Consumers Cognition of E-waste (CCEW)

Neisser (1967) has defined cognition as the mental process by which external or internal input is transformed, reduced, elaborated, stored, recovered and utilized. As such, it involves a variety of functions such as perception, attention, memory coding, retention and recall, decision-making, reasoning, problem-solving, imaging, planning and executing actions. In light of the present undertaking, the knowledge levels possessed by consumers towards recycling initiatives and the hazardous impacts of e-waste is verified. This is different from awareness levels, since it embraces a more solidified approach to conceptualization of the research problem in the psychological framework of consumers. We shall hereby seek to unfurl if consumer cognition of e-waste has a significant impact on consumer attitudes towards e-waste recycling activities. We may hypothesize this construct as:

H2: Consumer cognition is positively associated with consumer attitudes towards e-waste recycling.

Risk Perception of Consumers towards E-waste (CRPEW)

Weinstein (1989) has defined risk perception as the subjective assessment of the probability of a specified type of accident happening and how concerned we are with the consequences. Perception of risk transcends beyond the individual, and is a socio-cultural construct reflecting values, symbols, histories and ideologies. The present study regards risk perception towards e-waste as the idiosyncratic evaluation of e-waste as a trigger of climate change, environmental pollution and deteriorating human health. Like the previous cases, we shall seek to evaluate any significance between risk perception and consumer attitudes towards e-waste recycling, as hypothesized below:

H3: Risk perception of consumers has a favourable impact on consumer attitudes towards e-waste recycling.

Consumer Attitudes towards E-waste Recycling (CAREW)

Allport (1935) defined an attitude as a mental or neural state of readiness, organized through experience, exerting a directive or dynamic influence on the individual’s response to all objects and situations to which it is related. We shall seek to analyze whether consumers indeed have a predisposition towards recycling initiatives and whether these are favourable enough to influence recycling behaviour. This liaison has been hypothesized as:

H4: Consumer attitudes towards climate change has a positive influence on recycling behaviour of consumers

Exhibit 1.

Source: Author’s Own Conception.

E-waste Recycling Behaviour of Consumers (CRBEW)

In this part, we shall be delving into the behaviour displayed by consumers towards recycling initiatives. Former studies have borne testimony to the fact that there exists a clear gap between consumer awareness of the importance of e-waste recycling and the actual conduct of a recycling activity. We shall check whether this is validated in the context of our study or not. Further, we shall also test whether the risk perceptions of these consumers also influence recycling undertakings or not. Both of these statements have been hypothesized as follows:

H5: Awareness levels of consumers towards e-waste is positively linked to recycling behaviour of consumers.

H6: Risk perception of consumers has a significant impact on recycling behaviour of consumers.

These elements have been summarized and captured in the conceptual model illustrated in Exhibit 1:

Research Design and Methodology

The research design relates to the holistic strategy chosen in order to integrate the versatile components of the study in a coherent and logical pattern in an attempt to effectively address the research problem. We have categorized the research design under three heads to showcase the methodology adopted for the present study.

Data Collection Tools

For the purpose of this study, a structured questionnaire was developed comprising 23 questions, divided into five distinct segments. The questionnaire was largely self-designed, with certain questions being adopted from previous relevant researches on the exact domain. A 5-point Likert scale was developed to measure the responses and preferences of the respondents. The reliability of the questionnaire has been subsequently verified using Cronbach’s alpha for the standardized values of the items.

Survey Design and Sampling Tools

As noted afore, the study has been undertaken in the city of Kolkata, India. Adequate care has been taken to ensure that the respondents covered the major zones in the city, namely the north zone (Shyambazar area to Dum Dum area), east zone (Salt Lake, Rajarhat and New Town areas), west zone (Behala, Alipore and Kidderpore areas) and south zone (Ballygunge to Garia region). The purpose of conducting a stratified sample was to ensure a holistic representation of the city of Kolkata and gain responses quite equally. The sample size for the current study is 242 respondents. Questionnaires were initially administered to 253 respondents, but only 242 responses returned were complete, thus giving us a valid response rate of 95.7 per cent. The sampling method undertaken has been a blend of probabilistic and convenience sampling, since a fragment of the study had been conducted online as well, which generates responses believed to be rather judgemental in form. The relationships among the different variables were hence analyzed using IBM SPSS 23.0 and IBM SPSS AMOS 23.0 software packages.

Design of the Questionnaire

A structured questionnaire was designed for the study, comprising an aggregate of 23 questions, categorized across five segments, namely

Awareness of consumers towards e-waste (CALEW), which comprises four observed variables

Knowledge and cognition of e-waste levels (CCEW), which consists of six observed variables

Perception of risk towards e-waste (CRPEW), which encompasses three variables

Attitudes of consumers towards recycling of e-waste and climate change (CAREW), comprising six observed variables

E-waste recycling behaviour of consumers (CRBEW), which includes four observed variables

Majority of the questions are self-designed, with certain segments being derived from the studies undertaken by Akhtar et al. (2014) and Ercan and Bilen (2014) in Malaysia and Turkey, respectively. The questions, however, have been modified to suit the context of Kolkata, as well as other major cities in India. The questionnaire also incorporated the demographic profile of the respondents, including their zonal residential backgrounds, thereby giving us a holistic picture of the behavioural trajectories across the city of Kolkata.

Data Analysis and Findings

Based on the responses obtained from 242 respondents across the city of Kolkata, we shall analyze our findings to fulfil a wholesome comprehension of our objectives and gain valued insights about the behavioural trajectories of consumers towards e-waste and its recycling initiatives.

Demographic Profiling

We shall initially analyze the demographic profiles of the respondents in light of the present study. The study of demographics in relation to the present study shall enable us to understand the dynamic living populace in Kolkata, based on the obtained sample of respondents. This has been captured in Table 1.

The male–female ratio in our study is moderately balanced in the proportion of 53:47. The age group below 24 years, which comprises respondents from 15 to 24 years, has the maximum number of respondents (n = 95; 39 per cent). These respondents are largely expected to be students (n = 83; 34 per cent) and corporate executives or employees (n = 70; 29 per cent). Given their occupational attainment, the respondents mostly belong to the monthly income cluster of ‘Below ₹10,000’ (n = 93; 38 per cent). The respondents, as noted previously, have been chosen from four specific clusters in Kolkata, with the maximum number of respondents hailing from south Kolkata (n = 68; 28 per cent). The demographic profile, in a nutshell, reflects that the proportion of the youths are far more significant than their older counterparts and are engaged in education or corporate jobs.

Table 1.

Demographic Profile of Respondents

Demographic Construct	Classification	Population Statistics	Percentage
Gender classification of respondents	Male	129	0.53
	Female	113	0.47
	Total	242	1.00
Age group of respondents	Below 24	95	0.39
	25–35	83	0.34
	36–50	38	0.16
	Above 50	26	0.11
	Total	242	1.00
Occupation of respondents	Student	83	0.34
	Service (government sector)	41	0.17
	Service (corporate sector)	70	0.29
	Business/entrepreneur	43	0.18
	Others	5	0.02
	Total	242	1.00
Monthly income of respondents	Below `10,000	93	0.38
	`10,001–25,000	47	0.19
	`25,000–50,000	48	0.20
	`50,001–1,00,000	30	0.12
	Above `1,00,000	24	0.11
	Total	242	1.00
Zonal cluster of respondents	North Kolkata	57	0.24
	East Kolkata	63	0.26
	West Kolkata	54	0.22
	South Kolkata	68	0.28
	Total	242	1.00

Source: Author’s own computation.

Reliability Analysis

In order to test for internal consistency between the variables mentioned in our study, we have used Cronbach’s alpha. This measure shall help us in examining the scale reliability of the constructs used in the study. They have been displayed in Table 2.

The results indicate highly reliable results as is evident from the Cronbach’s alpha values, which are all above the ideal level of 0.7. The aggregate correlations of the corrected items are above the moderate level of 0.5.

Table 2.

Results of Reliability Analysis

Construct	Cronbach’s Alpha	Items	Total Correlation Value of Corrected Item	Cronbach’s Alpha When Item Removed
Total	0.996	23	—	—
Consumer awareness level towards e-waste	0.986	CALEW1	0.974	0.979
		CALEW2	0.952	0.985
		CALEW3	0.968	0.982
		CALEW4	0.969	0.980
Consumer cognition of e-waste	0.989	CCEW1	0.967	0.986
		CCEW2	0.941	0.989
		CCEW3	0.973	0.986
		CCEW4	0.969	0.986
		CCEW5	0.974	0.986
		CCEW6	0.953	0.888
Consumer risk perceptions of e-waste	0.978	CRPEW1	0.912	0.976
		CRPEW2	0.977	0.951
		CRPEW3	0.971	0.955
Attitudes towards e-waste recycling	0.983	CAREW1	0.955	0.979
		CAREW2	0.969	0.978
		CAREW3	0.930	0.982
		CAREW4	0.974	0.977
		CAREW5	0.962	0.979
		CAREW6	0.886	0.976
E-waste recycling behaviour of consumers	0.974	CRBEW1	0.966	0.957
		CRBEW2	0.877	0.973
		CRBEW3	0.954	0.960
		CRBEW4	0.959	0.959

Source: Author’s own computation.

Test for Convergent and Divergent Validity

Convergent and discriminant validity are regarded as subcategories or subtypes of construct validity. To establish convergent validity, we need to indicate that measures that should be related are in reality related. We have subsequently conducted a convergent validity analysis to test whether the items converge to measure a construct or not. The results are indicated in Table 3.

Table 3.

Analysis Results of Convergent Validity

Construct	Items	Factor Loading	AVE	CR
Consumer awareness level towards e-waste	CALEW1	0.944	0.951	0.858
	CALEW2	0.910
	CALEW3	0.960
	CALEW4	0.963
Consumer cognition of e-waste	CCEW1	0.977	0.925	0.959
	CCEW2	0.963
	CCEW3	0.973
	CCEW4	0.969
	CCEW5	0.975
	CCEW6	0.970
Consumer risk perceptions of e-waste	CRPEW1	0.974	0.951	0.854
	CRPEW2	0.967
	CRPEW3	0.965

Source: Author’s own computation.

The convergent validity of scale items were estimated by the respective factor loadings, composite reliability, and average variance extracted (AVE) (Fornell & Larcker, 1981). It is evident that the standardized CFA (Confirmatory Factor Analysis) loadings for all scale items have exceeded the minimum loading criterion of 0.7, and the composite reliabilities of all factors have also exceeded the recommended 0.7 level. In addition, the AVE values were all above the threshold value of 0.5 (Hair et al., 2006). Hence all three conditions for convergent validity were successfully met by the above measurement models.

Next, we have used the square root of AVE and the correlation coefficient matrix to test the discrimination validity of constructs. The discriminant analysis tests whether the construct is truly distinct from another construct or not. The results of the discriminant analysis have been captured in Table 4.

In the matrix, the values in the diagonal line represent the square root of AVE of the constructs, and other data present the correlation coefficient of the row construct and the column construct of the data. Only the path covariances between the three factors upon other factors were considered. Discriminant validity was obtained by comparing the shared variance between factors with the AVE from the individual factors (Fornell & Larcker, 1981). This analysis showed that the MSV and ASV between factors were less than the AVE for the individual factors. Square root of AVE greater than inter-construct correlations. Hence, discriminant validity was assured.

Table 4.

Analysis Results of Discriminant Validity

Construct	Inter-construct Correlations
Construct	CALEW	CCEW	CRPEW
CALEW	0.975
CCEW	0.974	0.962
CRPEW	0.951	0.950	0.975

Source: Author’s own computation.

Test for Structural Equation Modelling

According to Kline (2010), the rationale of constructing a measurement model relates to its aptness as a measurement instrument of the observed indicators, representing a latent variable. The same was reaffirmed by Hair et al. (2009), where it was observed that in measurement theory, the purpose is to estimate the liaison between the observed and the underlying latent variables. Bentler (1988) had noted that structural equation modelling (SEM) represents causal processes that generate observations on multiple variables.

In the present study, after having authenticated the reliability and validity of the data, SEM was performed to probe into the relationships between five key variables, namely, CALEW, CCEW, CRPEW, CAREW and CRBEW, all of which have been explicated earlier. The object was to test the fit between the proposed research model and the obtained data. This technique was chosen for its proficiency in simultaneously examining a series of dependence relationships, especially when there were direct and indirect effects among the constructs within the model (Hair et al., 2006). The preliminary stage in interpreting the SEM results encompassed a thorough review of fit indices, which provided evidence on how well the fit is between the data and the proposed structural model. In our present study, we used a maximum likelihood procedure as the basis for the SEM estimation. A similar set of fit indices was used to examine the structural model. Comparison of all fit indices with their corresponding recommended values provided evidence of a good model fit (χ2/df (Ratio of Chi-square to its Degrees of Freedom) = 2.08, GFI (Goodness of fit index) = 0.96, AGFI (Adjusted Goodness of fit index) = 0.94, CFI (Comparative Fit Index) = 0.98, RMR (Root mean square residual) = 0.32, RFI (Relative Fit Index) = 0.97 and RMSEA (Root Mean Squared Error of Approximation) = 0.04). This summary of model fit indices have been captured in Table 5.

Theory suggests that if the model fits the data well enough, we should hence review the feasibility of each path in the model by examining whether the weights are statistically significant and practically significant, which is evaluated on the basis of whether the effect size estimation (the R²) concerning a given path in the models are large enough.

Table 5.

Model Fit Indices for the Goodness-of-fit Measures

Goodness-of-fit Measure	Recommended Value	Actual Value of Measures	Result of Model Fit
CMIN/DF	≤3.00	2.077	Good
GFI	≥0.90	0.958	Good
AGFI	≥0.90	0.936	Good
NFI	≥0.90	0.967	Good
CFI	≥0.90	0.983	Good
RMSEA	≤0.05	0.042	Good

Source: Author’s own computation.

We have accordingly scrutinized the significance and strength of the hypothesized relationships in the research model. The results of the analysis of the structural model, including path coefficients, path significances and variance explained for each dependent variable presented in Exhibit 2.

Exhibit 2.

Source: Author’s own computation.

The above path validation diagram reflected the resultant path coefficients of the hypothesized research model. All of the six hypotheses were supported by the data entered into the model. Two endogenous variables were tested in the model and the results revealed that CALEW significantly influenced CAREW (β = 0.38, P < 0.05), supporting hypothesis H1. CCEW was observed to be significant in influencing CAREW (β = 0.91, P < 0.05), supporting hypotheses H2. Additionally, CAREW was significantly influenced by exogenous factor CRPEW (β = –0.34, P < 0.05), thus supporting hypothesis H3. However, the β-coefficient was negative, implying an inverse relationship between the constructs. Again, CRBEW was positively influenced by CAREW (β = 0.89, P < 0.05), thus supporting hypothesis H4. CRBEW was also seen to be significantly influenced by CALEW (β = 0.41, P < 0.05), thereby supporting hypotheses H5. However, CRBEW was not positively influenced by CRPEW (β = 0.41, P > 0.05), thus making hypothesis H6 unsubstantiated. A summary of the hypotheses testing results obtained from the path analysis is displayed in Table 6.

Table 6 reveals that all the hypotheses have been validated through the path analysis conducted as part of the SEM procedure. They have all been validated and we can conclude that awareness levels, cognitive parameters and risk perceptions are seen to favourably impact attitudes of respondents towards recycling, e-waste and climate change. The same can be said for the relationship between attitudes, awareness levels and recycling behaviour of respondents, which are all significantly associated. The only unsupported hypothesis is that of risk perceptions and recycling behaviours, which raises questions about their behaviour and the ecology.

Table 6.

Path Validation (Hypothesis Testing) Results

Hypotheses	Path	Coefficient	Direction	Results
H1	CALEW → CAREW	0.381	Positive	Supported
H2	CCEW → CAREW	0.913	Positive	Supported
H3	CRPEW → CAREW	–0.335	Negative	Supported
H4	CAREW → CRBEW	0.885	Positive	Supported
H5	CALEW → CRBEW	0.411	Positive	Supported
H6	CRPEW → CRBEW	0.588	Positive	Unsupported

Source: Author’s own computation.

Deliberation on Research Findings

The fundamental purpose of the undertaken research was to anatomize the relationship between societal behaviour towards the efficient management of e-waste, in terms of awareness levels and recycling behaviour. The study was a fresh effort to unravel the perceptions, attitudes and awareness levels of consumers in Kolkata to the skyrocketing rates of pollution triggered by indiscriminate e-waste disposal. Another rationale behind selecting Kolkata as the sample area is the fact that it is the fastest growing ‘hotspots’ of e-waste disposal across India. Given such an alarming scenario, it was important to understand the inherent psychology of consumers towards recycling initiatives and whether they were at all conscientious towards the mounting rate of e-waste in the city.

Our study revealed that consumer risk perceptions towards e-waste were inversely correlated to their attitude towards e-waste and climate change. This is a matter of concern, more than inconsistency in the study, because as the risk perceptions of consumers increase, their attitude towards recycling of e-waste declines proportionately. The plausible reasons for such a behavioural display could be attributed to an indifference among consumers and ‘inaction’ mind-set among them. Unless they are stirred by personal disturbances or societal disruptions, their perception of risk is likely to remain at a low and embryonic phase. The perceptions need to be strengthened through enhancing the level of absolute threshold such that the ‘just noticeable difference’ can be maximized.

Another cause of concern is the insignificant relationship between risk perceptions of consumers towards e-waste and the corresponding recycling behaviour. In terms of our hypothesis agreement, we must reject our stated alternate hypothesis and accept the null hypothesis, which states that ‘risk perception of consumers’ has no significant impact on recycling behaviour of consumers. It implies that the absolute threshold of consumers is too weak for them to respond to the stimuli (such as public health deterioration and rampant climate change) and convert it into a valid action. It could be attributed to a phase of sensory adaptation, where the stimuli which has become redundant or remains unchanged for an extended period of time. The key is to ensure that once a stimulus becomes detectable to us, we must take pertinent steps to recognize whether this stimulus changes. In other words, some kind of operant conditioning strategies must be undertaken to reinforce the behaviour of respondents when it comes to e-waste disposal or recycling. Children, for example, could be classically conditioned from a very germane stage into recycling initiatives, while organizations could positively reinforce compliant e-waste disposal mechanisms and negatively reinforce or even engage in punitive action against offenders. In simple terms, the perceptual levels of respondents towards e-waste must be strengthened to momentous levels, enough for all to take judicious win–win action, for themselves and their society.

Conclusive Remarks

Our study brought to light the fact that a sizeable proportion of the respondents are yet unaware of the rampant problems that e-waste has triggered in the environment as well as in human health. Therefore, there is a pressing requisite for a widespread educational campaign to disseminate and increase awareness among households. This could be steered by the state governments, corporate bodies or as a PPP (Public-Private Partnership) undertaking. The mantra is to successfully position the ills of e-waste disposal and the relevance of recycling behaviour in the psyche of the consumers. Further, it is also indispensable to ameliorate elementary education in environmental protection and resource conservation so as to foster e-waste recycling behaviour from childhood. Many higher educational institutions and universities in Kolkata, as well as in other states, have incorporated environmental studies as part of their curriculum, where students are required to experience a field trip in addition to their environmental education examinations. It has been observed that these field trips become picnics and photography sessions for most students and their escorted professors; examinations are merely meant for scoring marks and this becomes more of an obligation for the students as well as their professors. The need of the hour is to not to educate these youth, but to reveal before them real-life problems and hindrances across the city and the country, such that they internalize the problem instead of thinking of it as an onus. The study did unravel that awareness levels of the potential hazards of e-waste are very high among respondents, but the link to practice recycling behaviour is disengaged, which needs to be mended. There are numerous studies corroborating that awareness and knowledge levels positively influence public attitudes (Jim & Xu, 2002; Natura, 1995). Lin (2012) had explained that attitudes significantly influence pro-environment behavioural intentions. Hence, we could conclude based on such findings that awareness and knowledge have a greater impact on human attitudes that might consequent in positive behavioural changes.

Recommendations and Managerial Implications

There exists a plethora of prescriptive studies which preach an array of do’s and dont’s towards e-waste recycling behaviour. There are numerous conferences across the country that address the issue of e-waste, where thousands of research papers and articles speak of various strategies that could be undertaken to combat pollution from indiscriminate e-waste disposal. However, none of those symposiums or conferences have a ‘call to action’ session where some positive consensus is arrived at and at least one recycling initiative is successfully undertaken. Hence, this paper shall not prescribe any such do’s and dont’s, but solemnly advocate that action be taken at the individual level. Recycling initiatives, much like charity, begins at home and hence procurement of eco-friendly packages, refusing to use plastic bags or disposing e-waste to legalized processing centres in the city are some of the numerous individual-level strategies that must be undertaken with immediate effect. At the governmental level, WEEE imports must be banned immediately and an extended producer responsibility framework must be stressed, where the industry bears the brunt of products they place in the market. This is in accordance with the research conducted by Khetriwal et al. (2007), which threw light on the Swiss experience in utilizing EPR for E-waste management; in fact, a high compliance intensity can be achieved through independent control and monitoring, coupled with the collaborative initiative of all the stakeholders by providing several checks and balances, ranging from hard legislation to soft peer pressure. At the corporate level, business houses must be linked to ISO-compliant e-waste enterprises and consultants, such as E-Parisaraa or other state-aided enterprises. A group of vibrant youth based in Kolkata, opened up an e-waste management company called Avshesh, which is operational exclusively in the B2B space. These budding entrepreneurs are working on a retail model through which old cast-off electronic and electrical items can be collected from households. Interestingly, there is absolute competitive advantage since no company across the world has been able to match their business model. Attero is another promising start-up which spreads across India, picking up e-waste from more than 150 cities across five states in the country. Presently, it has over 450 clients, which includes corporate giants like Samsung, Wipro and HCL. The company recycles around 6,000 tonnes of electronic waste on an annual basis. Similarly, in the B2C segment, Bhopal-based Kabadiwala.com helps people book a slot and get their waste collected while actually getting remunerated for it.

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