An Assessment on Quality of Life and Happiness Indices of Project Affected People in Indian Coalfields

Abstract

Coal deposits are generally found in either riverine and/or beneath forest area. The coerced displacement of project-affected people (PAPs) for coal mining endangers the in situ conservation of their life/livelihood. It accounts for a heavy price against the mineral value mostly harvested by distant stakeholders. A study on quality of life (QoL) enroute happiness indices of PAPs is undertaken with reference to CSR/resettlement and rehabilitation initiatives undertaken by mining companies in coalfields of Jharkhand. This study aims to analyze elements influencing quality of life and happiness indices such as job/income opportunity, housing affordability, health security, infrastructure, social relations, environment sustainability, inclusivity, equity and diversity. Data were collected directly from PAPs using a questionnaire survey method and almost 501 responses received to assist in development of the model. Multivariate statistical analysis has been used with application of structural equation modeling methodology for data analysis. The result shows vital relations among the constructs introduced based on human, social, natural, physical and economical concerns. The findings also indicate inadequate resettlement and rehabilitation initiatives undertaken by project proponents towards restoring life quality. Thus, the conceptual framework customized to mining area is developed and validated for rendering a qualitative life-ecosystems to the PAPs.

1. Introduction

Coal continues to dominate as the prominent source of energy in India and makes significant contributions to the economic growth of the nation. It is plenteous in Jharkhand—a mineral- and forest-rich state of India. Coal as a primary fossil fuel resource contributes to about 80% of thermal power generation, and 30% of coal resources are stored in Jharkhand with some major coalfields such as Jharia, East and West Bokaro, Raniganj, Barakar, Karnpura, etc. Additionally, the region is nature-blessed, with land undulations, rivers, forests and geomorphology that render high-quality ecosystem services. Mining companies involved in mineral extraction seem to prioritize profitability, leading to unsustainable development eroding the cultural and ethnic fabric of local communities [1]. To achieve sustainable and inclusive growth, a balance has always been wanted by PAPs.

The people in eastern Indian states are mainly agriculture-oriented, and a shift from land location results in loss of vocation, livelihood pattern, cultural values and aesthetics. Together, it enters into realms of “Human Rights”, quality of life and happiness indices. The role of coal in the nation’s growth is eminent; however, it accounts for a heavy price on people (PAPs) residing in the vicinity. The prices account on land, forest, ecosystem services, livelihood and their life profile. Physical displacement, relocation and resettlement create tremendous risk for PAPs [2], and if not properly addressed by project proponents, can worsen life quality. History reveals that mining industries affected the environment due to their confrontation with nature, prioritizing profit over environmental impacts and inadequate rehabilitation initiatives [3]. The compensation packages given in lieu of acquired land are completely inadequate [4]. Involuntary displacement leads to violation of human rights, as the affected community gets deprived of various human rights such as right to food, water, shelter, job, health and education facilities, freedom of movement and security [5,6,7].

Resettlement policies and compensation packages are often inadequate in restoring normal life and livelihoods, and corruption in the system further exacerbates the problem [8,9,10,11,12,13]. Oliver-Smith [14] mentioned issues of inappropriate compensation packages and unjust resettlement procedures. This includes India [15], Bangladesh [13], Pakistan [16], Ghana [10,17,18], Nigeria [19], Sudan [20], Mozambique [21] and Sierra Leone [22].

Global mining companies had a discussion on the need of corporate initiatives to improve quality of life of PAPs [23] for building a sustainable community. Research on quality-of-life has been given due priority as an important value-added qualitative life measurement scale in national and international policies over the last 30 years [24,25,26].

Bhattacharya et al. [27] make an effort to understand the dilemma of development-induced displacement and draw beneficial and legitimate distinction between mainstream development and human development. The article focused on the holistic concept of development comprising quality of life in the context of food, cloth, shelter, condition for longevity of life and happiness [28]. Chakraborty and Narayan [29] emphasized the socio-economic perspective by mentioning the rights of education, right to livelihood, land rights and right to property. Adhikary et al. [30] highlighted the multiple dimensions or aspects of quality of life (QoL) from a socio-economic perspective and prepared a QoL index on the basis of a survey conducted in the Jharia coalfield region.

In 2015, NITI Aayog in India mentioned that displacement of people from mining areas and their vicinities has brought a big transition in QoL, specifically from a health perspective. It suggested prime responsibility of project owners towards improving overall environment conditions and quality of life. Yadav and Bhar [31] found through a review process that in the name of economic growth, the sovereignty and constitutional rights of displaced people are infringed. They also mentioned compensation, resettlement and rehabilitation measures as the fundamental right of those displaced. The recent literature on mining-induced displacement emphasized the human rights impact assessment, which should be based on UN guiding principles on business and human rights [32,33]. A human rights-based approach to resettlement (HRBAR) has also been outlined and suggested to companies for compliance to IFC standards (aligning with human rights perspective) for acquiring land and involuntary resettlement [32,34]. In the development process, the prime goal of promoting the well-being of PAPs remain elusive. This vulnerable group has to bear the cost of development by being deprived of their fundamental human rights [35]. According to Wilson [22], improving the socio-economic condition of resettled communities needs legislation; inclusion of landowners in determining modality for compensation of lost land, trees and crops; and rehabilitation of the mined-out area. Abankwa [36] identified infrastructure as the critical issue to be addressed given its high dissatisfaction quotient due to shallow infrastructural services rendered in Ghana. In their analysis, Khan et al. [37] exposed the legislative lacunae as well as negligence to the voice or priority of the displaced. Mandishekwa and Mutenheri [38] outlined displacement due to developmental projects and life satisfaction among displaced people in a post-displacement locality. They recommended that economists should emphasize studies based on mining- induced resettlement having the potential to resettle displaced people in a better way.

Against this backdrop, it may be concluded that studies undertaken in this arena focused mainly on mining induced displacement, inadequacy in resettlement and rehabilitation initiatives, human development indices and a penetration in human rights issues of PAPs. A few studies have attempted circumventing quality of life aspects but missed on account of its detailed attributes and, hence, its redress.

In this study, an attempt has been made to comprehend issues about PAPs in a holistic form wherein life quality becomes the central domain with happiness as an attribute expressed in metrics. A conceptual framework model may be helpful in enabling to provide a better life quality to PAPs under various mining business propositions.

To address the above mentioned research gap, the following research objectives have been framed: (1) to study the impact of CSR/rehabilitation and resettlement initiatives on PAPs undertaken by coal companies; (2) analyze factors attributed to quality of life and happiness indices; (3) analyze interrelationships and interdependence within factors influencing quality of life and happiness indices of PAPs; (4) assess quality of life and happiness indices through social instruments with primary data; and (5) develop a framework for quality of life and happiness indices customized to mining area.

The contribution of this study may be counted on its specificity towards mapping CSR practices conducted by coal companies vis-à-vis the overall well-being of PAPs. A human development matrix on functioning modes such as expressive, adaptive, integrative and conservative further unfolding into sub-systems such as personality, physical, social and cultural has been used to map attributes of quality of life. Human life quality is measured through evaluation of effectiveness of people in the aforesaid functioning modes on application of structural equation modeling (SEM). The variables used in SQoL are the subjective assessment of objective conditions. This could also be perceived as the functioning effectiveness of a person in different modes. In addition, SQoL indices on tangible measures, such as infrastructure, housing, health, job/income, etc., aim at capacity building of the society whereas the former help build PAPs capability. Finally, a conceptual framework customized to the mining area is developed and validated for rendering a qualitative life ecosystem to the PAPs.

To fulfill the above-mentioned research objectives, the related literature, research hypotheses and theoretical framework are presented in Section 2 and Section 3, respectively. Research methodology, description of study area and scale items are described in Section 4. The results of multivariate statistical analysis are presented in Section 5. Section 6 consists of conclusion and discussion. Finally, Section 7 comprises the novel outcome of this study with limitations, and Section 8 mentions limitations and the future scope of this study.

2. Materials and Methods

2.1. Theoretical Framework and Research Hypotheses

Quality of life can be interpreted as ‘the good’ life, where good stands for quality of life, evaluated subjectively and determined objectively through measurement of external conditions [39]. It is considered a vital indicator in assessing and monitoring the ecosystem services and social dimensions of sustainability as well [40]. Costanza et al. [41] presented an integrative definition of QoL. They integrated objective human needs such as socio-economic indicators with subjective well-being. Papageorgiou [42] suggested various methods appropriate to design quality of life indexes which can be used for evaluating quality of life aspects and compare them in different time or space frameworks. The various indicators for QoL have been categorized as air quality, water quality, noise quality, quality of soil and house, health, education, nutritional status, communication facilities, urbanization, socio-economic condition, recreation, security, natural conditions and hazards, etc. Bhattacharya et al. [27] make an effort to understand the dilemma of development-induced displacement and draw beneficial and legitimate distinction between mainstream development and human development. The article focused on the holistic concept of development which comprises quality of life in context of food, clothing, shelter, conditions for longevity of life and happiness [28]. Adhikary et al. [30] made an attempt to study and highlight the multiple dimensions or aspects of QoL from a socio-economic perspective. QoL index has been prepared on the basis of a survey conducted in Jharia coalfield region. Various issues of QoL covered are material, non-material and environmental dimensions. Narula et al. [43] documented the original social challenges of the mining area and how systematic steps could be taken by coal companies to uplift the life of affected communities. A livelihood generation framework through capacity building by allocating funds in CSR has been proposed. WBCSD [44] defined CSR as “business commitment to contribute to sustainable development, working with employees, their families, the local community and society at large to improve their quality of life”. A case of planning and implementation of capacity building initiatives in Muraidih coal mine of Jharkhand has also been presented for guidance to policy makers and business. The QoL index estimates the overall quality of life with the use of an empirical formula by taking into account eight different indexes [45].

The study considered Systematic Quality of Life Theory (SQoL) and model by Prof. Samuel Shye [46] for measuring quality of life and happiness level. Systematic Quality of Life model has been used for assessing the Quality of life and happiness indices of PAPs on the basis of CSR, rehabilitation and resettlement initiatives undertaken by coal companies. Systematic quality of life theory provides a rational method to generate quality of life variables encompassing human life quality. Human life quality is measured through evaluation of the effectiveness of people in observed functioning modes and compounding evaluations on application of appropriate statistical process. The variables used in SQoL are the subjective assessment of objective conditions. This could also be perceived as functioning effectiveness of an individual in different modes.

The application of SQoL in various research fields shows that it is a comprehensive model covering systematically the entire QoL content universe, exclusive in the sense of non-overlapping components and being balanced. SQoL indicators could be used for comparing the well-being of individual and community over time and across various locations under QoL assessment [47]. That is how this model has been considered appropriate for assessing quality of life as well as happiness indices of PAPs vis-à-vis initiatives under CSR, rehabilitation and resettlement schemes undertaken by coal companies. Various contextual variables extracted from the literature review on job opportunity, income opportunity, housing affordability, health security, infrastructure, social relations and environment sustainability contributing towards quality of life and happiness indices have been included for investigation. These variables may have interactions and correlations with each other; hence, these relationships have been further investigated by conceptualizing an integrative framework designed for examining causal relationship between these variables contributing towards quality of life and happiness indices of PAPs.

In relation to the research hypotheses, elements influencing quality of life of PAPs and happiness indices considered vital are job/income opportunity, housing affordability, health security, social relationships, infrastructure and environmental sustainability.

2.1.1. Job Opportunity

It is one of the crucial indicators of quality of life, contributing to an individual’s economic, societal, health and psychological stability. It brings psychological satisfaction by providing an opportunity to prove their capabilities and sense of achievement. It basically consists of determinants such as quality of job, employment rate and work–life balance (Voukelatou et al.) [48]. Objective well-being is usually measured through job, household income and consumption surveys [49]. According to Organization for Economic Cooperation and Development (OECD) [50] and ISTAT [51], major determinants for overall economic well-being are availability of jobs, income and wealth and consumption patterns. It is used by policy makers as a representative to avoid poverty and social exclusion.

Six prime indicators identified for objective well-being measurement are job opportunities, health, socio-economic development indicators, safety, environment and politics [50,51,52].

As an objective indicator of quality of life, job opportunity also contributes in achieving subjective dimensions of quality of life through fulfilling their desires. On the basis of the above discussion, the following hypothesis can be formulated:

H1. 

Job opportunity improves quality of life post-commencement of coal-mining project.

2.1.2. Income Opportunity

It is one of the key indicators and an objective dimension of quality of life. There are limited studies focused on objective quality of life [53,54], which positively stimulates the societal, economic and psychological well-being. This includes income, consumption composition, residence quality, transportation, education, social security, health care, life expectancy, public security, employment, etc. Two major determinants of economic well-being are income and wealth and consumption expenditure [50,51]. The purchasing power of an individual depends upon income; that is why it is also known as an important indicator of economic well-being [50] and contributes in overall quality of life. The quality of life of a community is usually measured through objective measures which include economic well-being (household income), health well-being (average life expectancy), environmental well-being (CO₂ emissions, climate change repercussions) leisure well-being (availability of parks, recreational facilities), etc. [55]. On the basis of these discussions, it could be hypothesized that

H2. 

Income opportunity improves quality of life post-commencement of coal-mining project.

2.1.3. Housing Affordability and Its Relationship with Job and Income Opportunity

Housing is one of the key indicators of QoL. Objective indicators of QoL are measured through wealth, income, consumption expenditure, condition of housing and its affordability, ownership of consumer durables, etc. Housing indicators reflecting the quality of life could be assessed through its quality, environment and cost indicators. Streimikiene [56] presented the concept of assessing housing as an indicator in the quality of life index. Housing conditions encompass its physical attributes as well as satisfaction level. The major issues considered for household selection depend upon its good condition and cost in many countries [57,58]. Most of the studies emphasized the dimensions of affordability, availability and quality. These aspects together are crucial to measure people’s housing needs. Few studies focused on safety, stability, environmental integrity and accessibility. Housing affordability is measured through the average cost for accessing a house on the basis of income. A quality job with high income plays a dominant role in affording a good quality house in a better locality. Income is considered statistically important in most of the literature on quality of life and well-being [59] as this can open doors for better education, health facilities, housing affordability, etc. The COMLE model [60] prefers the “vitality of housing” as a crucial housing indicator in a community’s economy. ‘Right to adequate housing’ is a human right which means it should be more than four walls and a roof over one’s head. The above discussion leads to the formation of the following hypothesis:

H3a. 

Job plays a dominant role in affording good quality house.

H3b. 

Income plays a dominant role in affording good quality house.

H3c. 

House affordability improves quality of life post-commencement of coal-mining project.

2.1.4. Health Security and Its Relationship with Job and Income Opportunity

Health is considered as a prime factor in quality of life as mentioned in a report published in 2001 by WHO Commission on Macroeconomics and Health and in 2000 by Lisbon Strategy for Growth & Jobs. Health security includes the “activities required to minimize the danger and impact of acute public health events that endanger the collective health of populations living across geographical regions and international boundaries” (WHO). It brings multiple benefits together which include job opportunities, community cohesiveness, better health ambience, increased life expectancy, infant survival, etc. Health services affordability depends on people’s ability to mobilize money as well as time needed for obtaining health services. Jeannie et al.’s study [61] in a Canadian context found that necessary health care services are not equally affordable for all and showed inequality on the basis of socio-economic status [62,63,64]. The results found reliability and validity of the measures developed by them as cost-barriers to medically necessary services, but validated gadgets are found discerning in urban areas compared to rural [65].

Public infrastructural facilities are somehow affordable but not of good quality; on the other hand, private health facilities are better but not affordable for displaced people because of low income, lack of insurance facilities and access. Health contributes significantly to the overall quality of life as mentioned in a report from 2001 by WHO Commission on Macroeconomics and Health. Health affordability is one of the most vital challenges influencing one’s ability to access health care. Initiatives for improving community capabilities and resilience to overcome any kind of disaster are still a keystone of national health security, as per Pfefferbaum et al. [66]. Income is considered statistically important in most of the literature on quality of life and well-being [59] as this can open door for better education, health facilities, housing affordability, etc. On the basis of the above discussion, the following hypothesis could be formulated:

H4a. 

Job plays a dominant role in availing health security.

H4b. 

Income plays a dominant role in availing health security.

H4c. 

Health security improves quality of life post-commencement of coal-mining project.

2.1.5. Infrastructure

Sustainable infrastructural facilities are the prerequisite for the quality of life of communities that use or are impacted by these facilities. Quality of life is described as a “multidimensional construct” [67,68,69], which includes natural capital, human capital, social capital and built capital (infrastructure).

Fischer and Amekudzi [70] reviewed the quality of life’s role in civil infrastructure decision making. Authors made an attempt to elaborate the importance of quality of life in infrastructure decision making for sustainable development. They used “infrastructure sustainability”, “sustainable infrastructure” and “sustainable infrastructure systems” through swapping. Authors suggested a new paradigm shift through consideration of infrastructure development as part of socio-technical system for achieving sustainability. On the basis of literature review of previous research, it could be found that social infrastructure has been considered as the “glue that holds community together” as mentioned by SGS Economics and planning in 2020. It also ensures satisfaction of basic human needs and development of state and its territories, as per Frolova et al. [71], and the quality of life of people residing there. On the basis of the above discussion, the following hypothesis has been formulated:

H5. 

Infrastructural facilities improve quality of life post-commencement of coal-mining project.

2.1.6. Social Relations

This is considered one of the prime components of subjective quality of life. It is conceived as the bonding and togetherness among the members of a community. In 2002, LGA, the inter-faith network’s ‘Guidance on community cohesion’ mentioned that as a conceptual framework, an attempt has been taken to measure the social relationship among community members based on the criteria of shared vision, inclusion of members from diverse background, equal opportunities and caring attitude.

Life satisfaction depends upon various life domains that include living situation, social relations, relationship with family, work, leisure, safety, health, finances and religion [72]; friendships, marriage, family life, standard of living, job, neighborhood, residence, housing, education, health and the self [73]. Researchers’ interest in social relationships started an era ago when the French sociologist Emile Durkheim hypothesized that disruptions in social linkages could affect psychological health. Positive social relationships have been found beneficial for cardiac health, endocrine, as well as the immune system [74]. Better social integration reduces diseases and mortality risks [75]. Social support interventions “mobilize the social environment” in meeting an individual’s needs better [76]. Social relationships put a strong impact on the psyche and physiology of an individual and, ultimately, their quality of life. On the basis of the above discussion, the following hypothesis has been formulated:

H6. 

Social relationship improves quality of life post-commencement of coal-mining project.

2.1.7. Environmental Sustainability

Environmental sustainability is basically associated with conservation of natural resources and protection of global and local ecosystem for the well-being of present and future generations. U.S. Environmental Protection Agency has defined it as “meeting today’s needs without compromising the ability of future generations to meet their needs.” It could be understood as responsible interactions with the environment, i.e., within the carrying capacity of nature to avoid depletion of natural resources and having sustainable environmental quality. In environmental psychology, individuals’ experiences with nature, associated activities and quality of life have been studied [77,78]. In environmental psychology, assessment of quality of life is done on the basis of various facets of physical environments such as pure air, quality of soil and availability of flora and fauna [79,80,81]. Environmental drives play a prominent role in quality of life and are excluded from human well-being accounts [82,83,84]. However, ‘ecosystem services’, the ecological characteristics and functions which contribute directly or indirectly to human well-being [82,85], were a specific subject of research for ecological economics right from the initiation [86].

The quality of life of a community is usually measured through objective measures which include economic well-being (household income), health well-being (average life expectancy), environmental well-being (CO₂ emissions, climate change repercussions), leisure well-being (availability of parks, recreational facilities), etc. [55]. A peaceful sound environment or sound scale contributes to an individual’s quality of life and reinforces the possibilities of recovery from psycho-physiological conditions [87]. On the basis of the above discussion, the following hypothesis could be formulated:

H7. 

Environmental sustainability improves quality of life post-commencement of coal-mining project.

2.1.8. Quality of Life

Quality of life has basically been described as a “multidimensional construct” [67,68,69]. It is also perceived as ‘the good’ life, where good stands for quality of life, evaluated subjectively and determined objectively through measurement of external conditions [39]. It is referred as an individual’s perception of their status in life on the basis of six variants or wide-ranging domains such as physical, environmental, social relationships, psychology, spiritual beliefs and independence [88]. It could be considered as different things for different people in different timespans [89]. Subjective well-being (SWB) findings in both national and cultural perspectives show interesting patterns. In their study of 55 nations on mean SWB levels, Diener, Diener and Diener [90] found that SWB is related strongly to income, human rights and societal equality. Recent studies on quality of life mainly focus on two distinct methodologies for measurement of quality of life. The first method is about measuring social and economic indicators for meeting human needs, and the other one is self-perceived level of happiness, satisfaction, meaning in life and subjective well-being [91,92].

Global mining companies had a discussion on the need for corporate initiatives to improve communities’ quality of life [23] for building sustainable communities. To mitigate the ecological, economic and social risk due to mining-induced displacement, various organizations are working under sustainable development framework for providing health and educational facilities, economic opportunities for compensation, royalties, livelihood and capacity building as well as community development program for PAPs [2,93].

QoL is considered a vital indicator in assessing the ecosystem services and monitoring the social dimensions of sustainability [40]. The practical approach of the research theme ‘well-being’ is gaining momentum as an instrument to understand the relations between ecological and social structures in developing countries [94].

The human ecosystem perspective has suggested a path for improving the QoL of communities [95,96]. As per the human ecosystem perspective for ensuring a sustainable community with good quality of life, equilibrium among environment, economy and social aspects needs to be maintained. Factors contributing towards quality of life include diversity of housing, end of sprawl, easy access to market transit, the widespread use of local products, community cohesiveness, sound economic base, entrepreneurship opportunities and equal opportunities. Quality of life is very much related to issues such as human rights, freedom and happiness [57,58]. Displacement caused by mining or any other developmental projects drastically affects the quality of life of the people displaced, which ultimately infringes upon their human rights.

“Happiness” and its relationship with quality of life:

Happiness has been taken as a construct from the above models on quality of life. It is an important goal of life [97] and explained by Anielski [98] as “…our genuine wealth”. As per the ancient view of Aristotle, “happiness is so important it transcends all other worldly considerations”. On the other hand, modern and psychological observations note that “happiness is for most men at all times, the secret motives of all they do…”.

Primarily, researchers measured quality of life objectively through per capita income, infrastructure, ambient air quality, etc. Later, however, they measured it through subjective indicators such as happiness, satisfaction with life, meaning in life, social or community cohesiveness, etc. [99]. It is basically the combination of natural capital, social capital, human capital and built capital. Subjective indicators of quality of life are gaining momentum. They emphasize self-reported or self-perceived levels of happiness, life satisfaction and meaning in life [91,92]. Evidence has been given by researchers for the validity of people’s perception for their well-being and quality of life [100]. Subjective indicators derived from reviews and perceptions while objective indicators derived through secondary data or evident facts [101].

Psychologists refer to happiness as subjective well-being and view it as satisfaction in different life situations, whether it is the case of displaced people from native places or any other situation. It could also be described as experiencing joy, satisfaction level and negativity [102,103]. Based on the above discussion, the following hypothesis has been proposed:

H8. 

The quality of life of PAPs influences their happiness level post-commencement of coal-mining project.

3. Proposed Conceptual Model

Subsequent to the literature review, various factors were identified and hypotheses were formulated for assessing quality of life and happiness indices of PAPs. Furthermore, on the basis of the existing relationship between various identified factors, the conceptual framework proposed for empirical validation is presented in Figure 1.

4. Research Study Area

India’s energy basket is rich with coal. Coal India Limited is the largest coal-producing government organization that produces around 800 MTY. The state of Jharkhand has three of its heritage subsidiary companies, BCCL, ECL and CCL, on account of geographical and anthropological concerns. Coalfields such as Ramgarh, Bokaro, Jharia and Raniganj have had a history of over 200 years of coal mining in India. Coal projects such as Rajrappa, Kusunda, Sijua, Mugma and Bajni under the command area of CCL, BCCL and ECL, respectively, were chosen for this study.

The present study on assessing the quality of life and happiness indices of PAPs has been undertaken in four mining areas as indicated in

Table 1. List of opencast coal mines selected for study in this research work.

Sl. No	Mining Areas	Coal Companies	Coalfields
1	Kusunda	Bharat Coking Coal Limited (BCCL)	Jharia Coalfield
2	Sijua	Bharat Coking Coal Limited (BCCL)	Jharia Coalfield
3	Rajrappa	Central Coalfield Limited (CCL)	Ramgarh/Bokaro Coalfield
4	Bajni (Mugma)	Eastern Coalfield Limited (ECL)	Raniganj Coalfield

.

Research Methodology

The complete research methodology has been conducted in two phases. Phase 1 started with the exploration of constructs, related dimensional variables and their relationship from various primary and secondary sources, research articles, theories, models, syndicated documents and government-published reports which were referred for literature review.

Furthermore, in Phase 2, subsequent to the exploratory studies, a conceptual framework was developed and empirically validated through a survey based on primary data, generated through face-to-face interview based on a set of structured questionnaire for capturing responses of the PAPs. Measurement scale items were adopted from the previous literature. Referred scales were rephrased to make them appropriate for capturing various dimensions in quality of life and happiness levels of PAPs. The first part of the questionnaire consisted of demographic profile of the respondents including age, gender, marital status, educational level, occupation of the respondent, annual earnings in Indian rupees, type of house they live in, etc. The second part consisted of 31 scale items to validate the proposed conceptual framework. The measurement scale based on the five-point rating Likert scale ranged from ‘Strongly disagree’ (1) to ‘strongly agree’ (5). In particular, four items were used to measure job opportunities, three each for income opportunities, health security, infrastructure, social relation and environmental sustainability and four each for measuring housing affordability, quality of life and happiness level to validate the proposed conceptual framework.

Table 2. Constructs and observable variables.

Variables	Measuring Item	Source of Adoption	Scale Reliability (Cronbach’s Alpha)
Job/Employment Opportunity
JO1	Coal-mining projects have increased the employment opportunities in my area	Patrick Arhin et al. [104]; Azadeh Lak et al. [105].	0.825
JO2	Coal-mining projects generate several types of job opportunities in my area
JO3	Increased coal-mining projects have minimized unemployment problems in my area
JO4	After increased coal-mining projects, a suitable job for me is easily available
Income Opportunity
IO1	Coal-mining projects have increased the income opportunities in my area	Patrick Arhin et al. [104]	0.837
IO2	Coal-mining projects generate several types of income opportunities in my area
IO3	Increased coal-mining projects have enhanced the level of income in my area
Housing Affordability
HA1	My housing affordability has increased to a great extent	Patrick Arhin et al. [104]	0.880
HA2	My housing affordability has increased to my level of satisfaction
HA3	My housing affordability has increased to my level of expectation
HA4	My housing affordability has increased to my level of desire
Health Security		Patrick Arhin et al. [104]	0.943
HS1	My health security has increased to a great extent
HS2	My health security has increased to my level of satisfaction
HS3	My health security has increased to my level of expectation
Infrastructure
INF1	After coal-mining projects, the infrastructure facilities such as streets, roads, water supply have improved to a great extent	FENERIA-M [106]; Davis et al. [107]; IISD [108]; Li et al. [109]; Potter et al. [110]; Hagerty et al. [111]; Santos et al. [112]; Psatha et al. [113]; Rezvani et al. [114].	0.913
INF2	After coal-mining projects, the infrastructure facilities such as streets, roads, water supply have improved to my level of satisfaction
INF3	After coal-mining projects, the infrastructure facilities such as streets, roads, water supply have improved to my level of expectation
Social Relations
SR1	After coal-mining projects, my relationship with the community people has improved to a great extent	A QoL Social Relationships scale, (Hawthorne et al. [115])	0.925
SR2	After coal-mining projects, my relationship with the community people has improved to my level of satisfaction
SR3	After coal-mining projects, my relationship with the community people has improved to my level of expectation
Environmental Sustainability
ES1	After coal-mining projects, environmental conditions in my area have improved to a great extent	Van Pelt [116]	0.786
ES2	After coal-mining projects, environmental conditions in my area have improved to my level of satisfaction
ES3	After coal-mining projects, environmental conditions in my area have improved to my level of expectation
Quality of Life
QL1	Pollution level decreased in our locality	Bubolz et al. [95]; Andrews, N. [117]; O’brien and Ayidiya [118]; Wagner [119]; Feldt [120]; Sustainable communities (New-brought) [121].	0.872
QL2	Economic activities improved in our locality
QL3	Health amenities have improved in our locality
QL4	Accessibility to work/school became easier
Happiness
HAP1	I am optimistic about the future	Hills and Argyle [122]; Argyle, Martin and Crossland [102]; Affec to meter 2: A scale to measure current level of general happiness, Richard Kannann and R Flett [123]; Tennant et al. [124]; Simmons [125]; S Stewart-Brown [126].	0.915
HAP2	I am always committed and involved
HAP3	My life is good
HAP4	I am satisfied with everything in my life

represents the scale items and constructs selected for the present study with the scale reliability coefficient (Cronbach’s Alpha). The scale items have an adequate reliability score for all the selected constructs of the research model.

Initially, the questionnaire was pre-tested and reviewed by experts from academia. On the basis of feedback, all corrections have been incorporated, such as typographical errors, layout and phrasing of the questionnaire. Furthermore, a pilot study was conducted by collecting data form 60 PAPs. Finally, the questionnaire comprises an introductory letter, introduction of the theme of the survey, demographic profile of the respondents and assessment items for constructs of the study.

The judgmental or purposive sampling technique has been used for identification of the survey pool. When the prime aim is to test the quality of life as well as happiness level of PAPs, these non-probability sampling techniques are used.

For data collected from primary sources, a structured questionnaire has been used for collecting data. In this research, the researchers purposefully visited selected coal mining areas for collecting data from PAPs. Data were collected through personal interviews from the PAPs of all four mining areas selected for the study. A total of 501 responses were collected through the questionnaire from the respondents, out of which 472 were found suitable for further analysis and were screened for data validation. The basic assumption for multivariate analysis is the fulfilment of normality condition, specifically in case of structural equation modeling. The normality test has been performed by calculating the skewness and kurtosis of variables. The values of skewness and kurtosis index were between ±3 and ±10, and no severe departure has been found. Thus, the present study satisfies the normality condition as all the values are within the acceptable range [127].

5. Results

The frequencies of the demographic variables viz. age, gender, educational level, marital status, occupation and income were analyzed. The highest frequency group belonged to the 25–35 years age group with 66% (n = 312). The second highest frequency was of the 36–45 years age group with 21% (96). It has been found that 107(23%) were female, and 365 (77%) respondents were male. The highest frequency of the respondents’ marital status was married with 60% (n = 280); 34% (162) were single; 4% (19) belonged to the separated category; and the remaining 2% (11) were divorced. Furthermore, 26% of respondents were illiterate; 120 (25%) respondents were matriculate; 100 (22%) were intermediate; 82 (17%) were graduate; 42 (9%) were postgraduate; and the remaining 7 (1%) belonged to other professions. Additionally, 34% of respondents were daily workers; 129 (27%) worked private services; 85 (18%) worked in government services; 68 (14%) worked in business; and the remaining 32 (7%) were contractual workers. The highest frequency income category belonged to Rs. 10,000 to 50,000 with 44% (n = 206). The second highest frequency income category, i.e., Rs. 50,001 to 100,000, consisted of 25% (n = 117); 16% (n = 79) were from the category Rs. 150,001 and above; and the remaining 15% (n = 70) were from the category Rs. 100,001 to 150,000.

Table 3. Demographics.

Age Group	Frequency	Percentage
25–35 years	312	66%
36–45 years	96	21%
46–55 years	20	4%
56 years and above	44	9%
Gender	Frequency	Percentage
Male	365	77%
Female	107	23%
Marital Status	Frequency	Percentage
Single	162	34%
Married	280	60%
Separated	19	4%
Divorced	11	2%
Level of Educational Qualification	Frequency	Percentage
Graduate	82	17%
Illiterate	121	26%
Intermediate	100	22%
Matriculate	120	25%
Other/Professional	7	1%
Post-graduate	42	9%
Occupation	Frequency	Percentage
Business	68	14%
Contractual worker	32	7%
Daily worker	158	34%
Government Service	85	18%
Private service	129	27%
Annual income (In Indian Rupees)	Frequency	Percentage
10,000 to 50,000	206	44%
Rs. 50,001–Rs. 100,000	117	25%
Rs. 100,001–Rs. 150,000	70	15%
Rs. 150,001 and above	79	16%

represents the demographic classification.

Statistical data reduction technique or factor analysis is used for grouping similar variable into a single broad aspect to avoid measurement overlap. Factor analysis is an essential procedure for reducing variables into small numbers of manageable factors. The results obtained through factor analysis consist of factor loadings. In this research work, principal component factor analysis has been used to identify the set of variables on the basis of strong correlation among them used to measure various non-observable constructs. A total of 31 measuring items were included for the measurement of different constructs related to quality of life and happiness indices. Varimax rotation was used for extracting factors; that helped in reducing the large number of variables into a smaller set of interpretable underlying factors.

Conceptual model measurement scales were tested by using EFA (Exploratory Factor Analysis) followed by CFA (Confirmatory Factor Analysis). EFA started with an initial analysis to obtain eigenvalues for each factor in the data. Subsequently, Kaiser–Meyer–Olkin (KMO) has been used to measure sample adequacy, and Bartlett’s test for construct validity was used to ensure that the data obtained for EFA are appropriate [128,129]. In order to carry out EFA, Bartlett’s test of sphericity ought to achieve statistical significance of less than 0.05. The results of Kaiser–Meyer–Olkin (KMO) and Bartlett’s test of sphericity have been considered satisfactory as the computed value of KMO was 0.797. This was above the required minimum thresholds of 0.7, and Barlett’s test of sphericity was also achieved (p < 0.05) [130]. Communalities among measured items loaded on the factor ranged from 0.575 to 0.948. The communalities for all variables were obtained more than 0.50, and this confirmed that there was no need to exclude any variables from further data analysis [128,129].

The EFA outcome shows that nine factors are aligned with our proposed theoretical model, which stated that quality of life and happiness indices of PAPs are attributed to seven factors. Thus, the EFA confirmed the retention of nine factors including happiness and quality of life (

Table 4. Component matrix.

Rotated Component Matrix a
	Component
	1	2	3	4	5	6	7	8	9
HAP1	0.885
HAP2	0.874
HAP3	0.869
HAP4	0.833
QL3		0.862
QL2		0.839
QL4		0.837
QL1		0.757
HA3			0.827
HA2			0.818
HA1			0.812
HA4			0.804
HS3				0.964
HS2				0.953
HS1				0.881
JO2					0.824
JO3					0.815
JO1					0.805
JO4					0.730
SR1						0.947
SR2						0.925
SR3						0.914
INF1							0.933
INF3							0.922
INF2							0.900
IO2								0.887
IO1								0.872
IO3								0.716
ES3									0.840
ES1									0.835
ES2									0.795

Extraction method: principal component analysis. Rotation method: Varimax with Kaiser normalization. ^a Rotation converged in six iterations.

).

Thus, the proposed conceptual framework for assessing the quality of life and happiness indices under rehabilitation and resettlement initiatives undertaken by coal companies for PAPs residing in coal-mining areas has been validated.

After checking the validity and reliability of scales, the hypotheses tested in the model followed. In this study, structural equation modeling (SEM) has been used for estimating the number of separate and interdependent variables; regression weights for each relation are presented in

Table 5. Regression weights.

			Estimate	Std. Estimates	S.E.	C.R.	p	Label
HAP1	<---	HAP	1.000	0.870
HAP2	<---	HAP	1.051	0.865	0.043	24.486	***	par_1
HAP3	<---	HAP	1.075	0.878	0.043	24.902	***	par_2
HAP4	<---	HAP	0.913	0.804	0.042	21.770	***	par_3
QL3	<---	QL	1.000	0.840
QL2	<---	QL	0.974	0.807	0.049	19.951	***	par_4
QL4	<---	QL	0.929	0.803	0.047	19.864	***	par_5
QL1	<---	QL	0.832	0.707	0.049	16.831	***	par_6
HA3	<---	HA	1.000	0.828
HA2	<---	HA	0.982	0.766	0.054	18.212	***	par_7
HA1	<---	HA	0.990	0.814	0.051	19.588	***	par_8
HA4	<---	HA	1.021	0.809	0.052	19.788	***	par_9
HS3	<---	HS	1.000	0.997
HS2	<---	HS	0.978	0.967	0.015	63.915	***	par_10
HS1	<---	HS	0.754	0.802	0.027	28.106	***	par_11
JO2	<---	JO	1.000	0.781
JO3	<---	JO	1.090	0.773	0.069	15.689	***	par_12
JO1	<---	JO	0.885	0.745	0.059	15.097	***	par_13
JO4	<---	JO	0.775	0.650	0.058	13.349	***	par_14
SR1	<---	SR	1.000	0.957
SR2	<---	SR	0.944	0.892	0.030	31.206	***	par_15
SR3	<---	SR	0.937	0.845	0.034	27.647	***	par_16
INF1	<---	INF	1.000	0.934
INF3	<---	INF	0.964	0.887	0.034	27.974	***	par_17
INF2	<---	INF	0.911	0.828	0.037	24.814	***	par_18
IO2	<---	IO	1.000	0.915
IO1	<---	IO	1.017	0.938	0.042	24.365	***	par_19
IO3	<---	IO	0.456	0.545	0.035	12.869	***	par_20
ES3	<---	ES	1.000	0.746
ES1	<---	ES	1.232	0.758	0.094	13.061	***	par_21
ES2	<---	ES	0.969	0.733	0.075	12.978	***	par_22

*** = p < 0.001.

.

Furthermore, structural equation modeling (SEM) was used for validating the conceptual model (Figure 2) developed as a framework on the validity and reliability of the construct. The statistical package for social science (SPSS 23.0) and other statistical tools such as AMOS 21 were used for hypotheses testing. Advanced Excel 2010 or ATLAS.ti 8 software was also used to perform the statistical analysis.

As per the recommendations of Anderson and Gerbing [131], theoretical structure was evaluated by using goodness of fit indices. The constructs used in the proposed conceptual framework obtain minimum reliability and validity criteria (measurement model) which further allow the structural model to be applicable (

Table 6. SEM model—fit indices values.

Fit Indices	Values
Chi-square to degrees of freedom Ratio (CMIN/DF)	2.08 (877.679/422)
CFI	0.952
NFI	0.912
RFI	0.904
TLI	0.947
RMSEA	0.043

).

The fitness indices for the proposed model were found within the acceptable range. The R-squared values for housing affordability (HA), health security (HS), quality of life (QL) and happiness (HAP) were 0.117, 0.021, 0.254 and 0.010, respectively. However, the low value of R-square for a significant model does not have impact on fitness of structural relation [132].

The value of CR has been calculated to determine the Convergent Validity. AVE was used to determine the item’s loading average variance. To ensure convergent validity, the following criteria need to be satisfied: CR > 0.7, AVE > 0.5 and CR > AVE. The values for CR are in the acceptable range for all the constructs. Values in Table 6 confirm the convergent validity of model. The discriminant validity of the model is determined by comparing the amount of variation captured by the construct (AVE). The square root of the AVE levels for each construct is higher than the correlation between the constructs, indicating the discriminant validity (

Table 7. Discriminant validity.

	Sqrt AVE	IQ	HAP	QL	HA	HS	JO	SR	INF	ES
IO	0.819	1.000
HAP	0.855	0.189	1.000
QL	0.797	0.467	0.082	1.000
HA	0.806	0.132	0.511	0.156	1.000
HS	0.926	0.116	0.098	0.188	0.108	1.000
JO	0.740	0.187	0.121	0.232	0.342	0.117	1.000
SR	0.899	−0.087	−0.038	−0.069	0.066	−0.011	−0.012	1.000
INF	0.884	0.071	−0.035	0.105	−0.113	0.007	0.012	−0.152	1.000
ES	0.746	0.085	0.162	0.216	0.179	0.199	0.177	0.061	0.040	1.000

).

Table 8. Result of hypothesis testing.

Hypotheses	Relation	Estimate	Sig.	Result
H1: Job opportunity improves quality of life due to CSR initiatives post-commencement of coal-mining project	QoL<---JO	0.145	0.032	Accepted
H2: Income opportunity improves quality of life post-commencement of coal-mining project	QoL<---IO	0.623	***	Accepted
H3a: Job plays a dominant role in affording good quality house	HA<---JO	0.431	***	Accepted
H3b: Income plays a dominant role in affording good quality house	HA<---IO	0.122	0.094	Rejected
H3c: House affordability improves quality of life post-commencement of coal-mining project	QoL<---HA	0.051	0.312	Rejected
H4a: Job plays a dominant role in availing health security	HS<---JO	0.152	0.041	Accepted
H4b: Income plays a dominant role in availing health security	HS<---IO	0.169	0.037	Accepted
H4c: Health security improves quality of life post-commencement of coalmining project	QoL<---HS	0.089	0.022	Accepted
H5: Infrastructural facilities improve quality of life post-commencement of coal-mining project	QoL<---INF	0.047	0.109	Rejected
H6: Social relationship improves quality of life post-commencement of coal-mining project	QoL<---SR	−0.026	0.445	Rejected
H7: Environmental sustainability practices of coal-mining project improve quality of life	QoL<---ES	0.142	0.074	Rejected
H8: The quality of life of PAPs influences their happiness level post-commencement of coal-mining project	HAP<--QoL	0.111	0.040	Accepted

*** = p < 0.001.

illustrates the results of hypothesis testing.

The structured equation modeling (SEM) results into multivariate hypotheses testing on quality of life leading to their happiness indices. There are 12 hypotheses based on job opportunity, income opportunity, housing affordability, health security, infrastructure, social relationship, environment sustainability in totality on which QoL and happiness have been validated with primary data generated from PAPs across various coalfields viz. Raniganj, Jharia and Bokaro in Jharkhand. M/s Coal India Ltd. under its various subsidiary companies has taken initiatives under CSR/RR schemes to address existing and emerging issues in due course of mining to PAPs.

It is quite imperative to note from the results that issues pertaining to job, income and health security have been duly addressed as a systematic approach adopted by coal companies under CSR schemes with issues such as environment, housing, infrastructure and social fabric demand further attention.

From Table 8, it can be concluded that there is a positive relationship between availability of job opportunities in the location and improved quality of life of mining project-affected people (H1). In the same context, improvement in the job market enhances the income level and, in turn, also improves the life quality in the coal-mining area (H2). Hence, it has been statistically established that job plays a dominant role in affording quality of housing facility (H3a). However, the analysis rejects the assumption that income plays a dominant role in affording good quality house (H3b), and only house affordability improves quality of life post-commencement of coal-mining project (H3c). There are other factors that have an impact on the improvement of quality of life for project-affected people (PAPs). Hence, the hypothesis that infrastructural facilities improves quality of life post-commencement of coal-mining project was rejected (H5). The result from Table 8 depicts that job and income play a significant role in availing health security (H4a and H4b), and as a result, health security improves quality of life post-commencement of coal-mining project (H4c). The impact of social relationship and quality of life post-commencement of coal-mining project is also rejected by statistical result (H6). Moreover, the hypothesis testing the assumption that environmental sustainability practices of coal-mining projects improve quality of life (H7) is also rejected. Overall, the assumption that the quality of life of PAPs influences their happiness level post-commencement of coal-mining project (H8) is accepted. The rejection list on account of housing and infrastructure tells about its inadequacy and a mismatch with community needs. Structural equation modeling (SEM) helped in model-fit and hypotheses testing. The results reflect acceptance of seven and rejection of five (out of twelve) hypotheses framed for quality of life which shows a marginal improvement in quality of life (H8) of PAPs post-commencement of coal-mining projects.

6. Conclusions and Discussions

Coal deposits are generally found in riverine and forest areas and grow with ethnic ecosystems. This invites for developing the art and science of mining to render a sustainable/inclusive growth. Mining activities are conducted in apparent confrontation with nature and account for a heavy price on PAPs. The price accounting for land, forest, ecosystem services and life profile is mostly borne by the people residing in the vicinity rather than those harvesting its rewards. History reveals that mining industries affected the environment by being in confrontation with nature, prioritizing profit over environmental impacts and implementing inadequate rehabilitation measures [3]. Physical displacement, relocation and resettlement create tremendous risk for the PAPs [2], and if not properly addressed by project proponents, worsen the life quality of PAPs. This also encroaches into the realms of human rights of PAPs undergoing displacement without adequate resettlement and rehabilitation proposals, compensation and social security endeavors [133,134]. The forced eviction of people due to development projects is considered a violation of human rights [135], and they have the right to be resettled [5,136]. The compensation given for lost land is inadequate to address the loss of life and livelihood, necessitating a renewed focus on human rights issues [4]. Forced displacement, from ancestral lands without appropriate rehabilitation measures, constitutes a violation of human rights and should not be tolerated [137]. The cost involved along with the resettlement process and life of PAPs after displacement should be compliant with human rights expectations, and for that, improvement in well-being is required [136].

It has been further thought of that mining operations should be conducted in such a way that social, economic and environmental parameters are constantly considered critical as triple bottom-line for sustainability. Today, the challenge before mining industry is to observe a dynamic balance among the social, economic and environmental dimensions minimizing degradation [138]. In view of this, mining conduct in alignment with nature and inclusivity needs to be explored. The studies done so far in this area miss to account for QoL and to adequately address happiness indices, touching upon livelihood issues and connecting to life and its quality. An attempt has been made to comprehend holistic life quality under the broad domain of QoL leading to happiness and prepare a model conceptual framework which will be helpful in providing a dignified quality life to PAPs.

The statistical analyses conducted under the QoL model render insights into the life and livelihood of PAPs. The structured equation modeling (SEM) results into multivariate hypotheses testing for quality of life leading to happiness indices. There are eight (8) hypotheses based on job opportunity, income opportunity, housing affordability, health security, infrastructure, social relationship, environment sustainability in totality on which QoL and happiness have been validated with primary data generated from PAPs across various coalfields viz. Raniganj, Jharia and Bokaro in Jharkhand. M/s Coal India Limited under its various subsidiary companies has taken initiatives under CSR schemes to address PAPs regarding existing and emerging issues in the due course of mining.

It is quite imperative to note from the results that issues pertaining to job, income and health security have been duly addressed as a systematic approach adopted by coal companies under their CSR schemes while issues such as environment, housing, infrastructure and social fabric demand due attention. The rejection list on account of housing and infrastructure tells about its provisioning inadequacy and a mismatch with community needs. The SEM results, though, stand accepted but with a thin margin of 7:5 that promises learning galore for companies to derive and suitably evolve CSR schemes with evolving concerns. Coal companies need to comprehend hyperlinked stories hidden in primary data and reframe their need-assessment surveys to higher levels to address issues of externalities, ecosystem services, biodiversity, quality infrastructure, housing, recreational dimensions, mapping of social fabric and cultural life with data analytics deliberation.

The study of social, ecological and economic impact on the life and livelihood of PAPs is conducted in coal-mining projects spanning over the length and breadth of coalfields in Jharkhand. It stretches from Bokaro to Raniganj including Jharia coalfields with an area of over 1000 sq. km being worked by three major coal companies, CCL, BCCL and ECL, of the coal behemoth M/s Coal India Ltd.

The focus of the present study has been centered around the impact of CSR/rehabilitation and resettlement initiatives undertaken by coal companies on people in terms of mapping the induced changes in life quality and livelihood of PAPs. In an attempt to address their quality of life and happiness indices, various factors attributed to quality of life such as job opportunity, income, health security, housing affordability, infrastructure, social relationship and environmental sustainability are introduced based on human, social, natural, physical and economical concerns.

The factors aforesaid have been studied for interrelationships and interdependence influencing life and its quality leading to happiness indices of PAPs affected due to coal mining. The study tells that the inter-relationship among life indicators such as job opportunities rendered to PAPs plays a dominant role in their capability to afford a good house and avail health facilities. The statistical analyses testing for hypotheses suggest that income does not play a significant role towards ensuring good quality house (H3b); however, it contributes to availing health security. Infrastructural facilities provided by coal-mining projects are also found non-contributing in improving the life quality (H5). Further, the societal dimension has been found to be non-influential towards their quality of life (H6).

Environmental and sustainability practices/initiatives of coal-mining projects are not found to contribute to improving quality of life of PAPs(H7) for the obvious reason of their misappropriate priorities for the economic exploitation of minerals at the cost of ecosystem services. Together, this affects ethnicity and the social fabric in view of enhanced externalities due to project reasons.

The result obtained from this study aligns to the study conducted by Bhattacharya et al. [27], who make an effort to understand the dilemma of development-induced displacement and draw beneficial and legitimate distinction between mainstream development and human development. The authors focused on the holistic concept of development comprising quality of life referring to food, clothing, shelter, condition for longevity of life and happiness [28]. Adhikary et al. [30] highlighted the multiple dimensions or aspects of QoL from a socio-economic perspective and prepared a QoL index on the basis of survey conducted in the coalfields. Various other issues of QoL covered are material, non-material and environmental dimensions. These studies have touched the quality of life to some extent but have not tried to assess the CSR, resettlement and rehabilitation initiatives undertaken by mining project owners. In this study, the aspects of quality of life and happiness indices of project-affected people have been addressed on the basis of CSR, resettlement and rehabilitation initiatives undertaken by project proponents. This study has practical implications for policy-making, particularly in improving the resettlement and rehabilitation initiatives for the project-affected people due to coal mining or any other infrastructural or development projects. These outcomes can guide improvements in corporate social responsibility initiatives by mining companies and other corporates.

7. Theoretical Implication and Novel Outcome of the Study

The available literature shown in the current study has paved a way towards conceptualizing and validating an integrated conceptual model assessing quality of life (QoL) and happiness indices of PAPs on the basis of CSR, resettlement and rehabilitation initiatives undertaken by coal companies.

The Systematic Quality of Life (SQoL) theory and model of Prof. Samuel Shye [46] has been further extended by using its application for assessing the life quality and happiness domain of project-affected people. The novelty of this study may be counted on its specificity towards mapping CSR practices conducted by coal companies vis-à-vis the overall well-being of PAPs. The human development matrix on functioning modes such as expressive, adaptive, integrative and conservative further unfolding into sub-systems such as personality, physical, social and cultural has been used to map attributes of quality of life. Human life quality is measured through evaluation of effectiveness of people in the aforesaid functioning modes on application of structural equation modeling (SEM). The variables used in SQoL are the subjective assessment of objective conditions. This could also be perceived as functioning-effectiveness of a person in different modes. In addition, SQoL indices on tangible measures such as infrastructure, housing, job/income, etc., aim at capacity building of the society, whereas the former helps build PAPs capability. Together, this would lead to an inclusive growth model on quality of life and happiness.

Thus, a conceptual framework customized to mining area has been developed for a qualitative life which will be helpful for mining project proponents while planning their CSR, resettlement and rehabilitation policies and schemes in a holistic manner as suggested herein this model. The quality of life of PAPs undoubtedly directly influences their happiness indices.

8. Limitations and Future Scope of the Study

The Human Functioning Model [4 × 4 table] is a function of time, space and status of social well-being. A social instrument capturing various functionality may suitably evolve to capture inputs on various frames/layers that overlap on time and space. An assessment across thematic cross-section leveraging data science and AI techniques may render a deeper insight into PAPs’ holistic functionality and their comprehension.

Additionally, a regenerative economy model needs to be worked upon in detail with social entrepreneurship, tribal enterprising and forest entrepreneurship in mind matching with ethnic skills that go beyond thinking of mere livelihood provisions such as job, income, etc. Despite its contributions, this study has a few limitations that could be addressed in future research. It could benefit from a comparison with other similar regions, both within and outside India, to understand the wider context of the issues faced by PAPs. Furthermore, this study primarily relies on data from questionnaires, which can be subject to respondent bias. Triangulating these results with data from other sources, such as interviews or observational studies, would strengthen the findings.