Abstract
Land acquisition and resetlement are sensitive issues because of its large impacts on the life of local people and communities, especially in developing nations. In Vietnam, recently, land acquisition is increasingly popular to serve infrastructure development and socio-economic projects. This study aims to identify factors affecting household environmental satisfaction after land acquisition and resetlement in Hai Phong city. The empirical study model is proposed based on theoretical model by Shin (2016) and empirical studies on environmental satisfaction. We conducted 2 focus group discussions with stakeholders and a survey sample of 585 households in 03 resetlement areas to collect data. Cronbach' Alpha test, exploratory factor analysis, and multiple regressions were used for data analysis. Results showed 6 main factors affecting the extent of respondents' environmental satisfaction after land acquisition, including employment and income, local government, public services and facilities, social networks, environment and health and education. Among them, employment and income is strongest impact factor. From the results, some solutions were proposed to increase satifactions and stabilize livelihoods for people after land acquisition in Hai Phong and Vietnam.
Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
1. Introduction
Land is one of the most important basic assets of humanity (Ellis 2003, Gui et al 2021, Dang et al 2021). Although land ownership is tied to wealthy and powerful individuals and organizations in many societies, everyone, rich or poor, needs at least land for livelihood and shelter (Roy 2014, Dong et al 2020, Gui et al 2021). For several communities, the land rights of the poor are weakened by land tenure insecurity. Even governments that are supposed to serve the people often find themselves in conflict with their citizens because they interfere with their land rights. To meet rapid urbanization and the need for decent housing, governments have embarked on urban development projects such as building infrastructure, developing satellite towns, building apartment buildings or promoting other urban development investment activities (Martin et al 2013, Gere and Schimmack 2017, He and Ahmed 2022). Most of these projects involve land acquisition on the periphery of urban centers. In other cases, authorities reclaim land as part of infrastructure development. This land is mainly owned by local people in these areas, most of whom are poor (Chambers and Conway 1992, Callaghan and Colton 2008, Hoogerbrugge and Burger 2018, Le and Nguyen 2019).
For an agricultural country with about 70% of the population being farmers like Vietnam, land is always a very sensitive issue and receives special attention from the entire society (Le et al 2020, Tuan 2021). Especially, when the country transitions to a market economy, the State implements a new land management mechanism by identifying households as autonomous economic units in agricultural and forestry production; carry out land allocation and land lease to households and individuals for long-term stable use (Tuan and Hegedűs 2022). It is this change in management mechanism that has returned land to its inherent value: Land becomes increasingly valuable and is exchanged on the market; used as collateral in credit relationships as mortgage loans with banks and credit institutions; allowed to contribute capital to joint ventures in production and business. People are increasingly aware of the great value of land (Le et al 2020, Dat and Truong 2020).
Since the Renovation (Doi Moi) (1986), along with policies to create conditions for urban development, Vietnam's urbanization process has made significant changes. In the period 2000–2010, Vietnam began to accelerate the pace of urbanization. In terms of space, Vietnam's urban areas increased by 2.8% annually, among the countries with the fastest growth rate in the region (Le and Nguyen 2019). Regarding urban population growth, the growth rate is more than 3%/year. Vietnam is one of the countries with rapid urbanization in East Asia. Each year, it is estimated that Vietnamese urban areas add from 1 to 1.3 million people. (Dat and Truong 2020). By 2021, the national urbanization rate has reached about 41.5%, with 888 urban areas). High urbanization speed comes with the need to build infrastructure, industrial parks, urban areas and utility spaces. Therefore, land acquisition has become common in many urban areas (Tuan 2021, Tuan and Hegedűs 2022). Vietnam has taken many institutional and legal steps for land acqusition, compensation and resettlement. The Land Law (2013) clearly stipulates the principles and processes of land acquisition, site clearance, compensation and resettlement. Sub-law documents and in each locality further concretize the Land Law into specific regulations, specific to the locality.
With land becoming more and more valuable, the issues of land recovery, compensation, and site clearance also face many difficulties and complications. In many cases, people do not agree with the State's compensation plan and refuse to hand over land, leading to a slowdown in construction progress, directly affecting the interests of investors and causing serious negative impact on the investment environment (Tuan 2021). Furthermore, due to disagreement with the compensation plan, people whose land was recovered conducted prolonged lawsuits, filed lawsuits in large numbers, and filed lawsuits at high levels, causing political instability and social order and safety. Disputes and complaints related to compensation when the State recovers land tend to increase in both number and severity and complexity. In the three years 2019–2021, the Government Inspectorate has counted 550,000 land acquisition disputes among farmers nationwide, with an average of over 200,000 disputes per year (Government Inspectorate 2022). Injustice leads to instability, which also negatively affects the investment environment and business environment of Vietnam in general. This shows that we need to continue to research and learn about residents' satisaction after land acquisition, compensation mechanism and resettlement supporting policies in order to improve land acquisition process and practice (Dat and Truong 2020, Tuan 2021, Tuan and Hegedűs 2022).
This study fills in this gap by focusing on the analysis of households' environmental satisfaction after land acquisition in Hai Phong city, one of the 5 largest urban areas in Vietnam. The study contributes to the literature on land acquisition and people's satisfaction. At the same time, it contributes to providing implications for improving the process and impact of land acquisition in Vietnam as well as developing countries. The structure of the article includes: after the introduction is the theoretical framework and model development (section 2). Section 3 presents data collection and analysis model. Section 4 shows study results and section 5 presents discussions and comparison with related literature. Part 6 is the conclusion with implications for improving environmental satisfaction of residents after land aquisition.
2. Theoretical framework and model development
2.1. Theoretical framework of environmental satisfaction
Environmental satisfaction is a complex category that has been extensively studied both theoretically and empirically in recent years (Ibem and Aduwo 2013, Huang and Du 2015, Gui et al 2021). Environmental satisfaction is the subjective assessment of an objective state of the environment and considers how well the environment satisfies the needs and expectations of the individual (Shin 2016, Hoogerbrugge and Burger 2018). Because individuals' expectations and values are subjective and different at different times, assessing satisfaction is not simple, depending on the circumstances and assessment goals (Galster and Hesser 1981, Goldstone and Barsalou 1998, Mesulam 1998, Arneson 1999). The objective quality of the environment itself is not easy to quantify and evaluate because it depends on the objective standards of the external environment as well as the social consensus of each place of residence (Shin 2016, Luo and Timothy 2017, Tong et al 2019).
According to Shin (2016), environmental satisfaction is theoretically related to three aspects. First, the environment includes physical elements, space and social relationships. Some previous studies have evaluated both natural and social factors to present a full picture of environmental satisfaction. Some studies only focus on one of the two aspects, but they also acknowledge in their limitations that the assessment should be expanded to include both factors. Research has not yet clearly shown which factor trends are more important in determining an individual's environmental satisfaction (Bandura 2006, Calmeiro et al 2018, Dai and Zhao 2020).
Second, each physical and social element is organized in a network and consists of many different layers. This organizational network can have many spatial and social levels, from within the residential premises, to neighboring spaces, communities, ecosystems and economies (Shin 2016). An individual is related to the environment through an intricate network of relationships structured into interrelated layers. Each of these layers has a certain impact on the individual's environmental satisfaction at a time and is a dynamic system (Amerigo and Aragones 1997, Callaghan and Colton 2008, Dinc et al 2014).
Third, measuring physical and social factors can be through objective or subjective measures (Amerigo and Aragones 1997, Arneson 1999, Demirbatır et al 2013). This is also a controversial topic in research (Dong et al 2020). Because some authors believe that measuring environmental quality must be based on objective scales, these scales may even depend on institutional conditions and specific standards. Some other authors believe that satisfaction lies in the subjective feelings, perceptions and feelings of individuals, so it can be measured through subjective scales but requires strict testing and delineation into specific constructs (Ibem and Amole 2013, Dong et al 2020). Some recent studies suggest that the subjective scale is more powerful because it takes into account personal characteristics and feelings of each person in the community about the environment (Mesulam 1998, Makinde 2015, Dong et al 2020). However, some other authors believe that measuring satisfaction needs to be through both groups of scales to fully reflect the economic, social and environmental aspects of individuals and settings (Kley and Dovbishchuk 2021, Lu et al 2021, Li et al 2022). According to Mesulam (1998), each individual belongs to one place at one time and places include physical parameters and behavioral parameters (referred as cognitive ecology).
As to Shin's theoretical model (2016), in a place, social organizations create physical structures as well as participate in shaping social structures and interactions, through regulations or norms (rules of place). In this model, physical structures will shape individual behaviors through spatial and physical use values, for example shopping behavior at local malls or playing sports at football fields. The physical structure also underpins cognitive ecology. Physical structures have clear boundaries and individual behavior not only lies within those boundaries but is shaped by the boundaries and the visible rules within the boundaries. An individual will feel dissatisfied if the physical structures and social relationships in their place are restrictive, difficult to regulate, and do not help them optimize their interests and expectations. Individuals will choose 1 of 4 strategies to increase their satisfaction including (i) adjusting environmental factors including both personal and social, (ii) adapting to environmental factors, (iii) adjusting perceptions and expectations about the environment, and (iv) getting out of that place (Li et al 2014, Shin 2016) (figure 1).
Figure 1. Physical and social structure at a setting place. Source: Adapted from Shin (2016).
Download figure:
Standard image High-resolution imageIn addition to the above theories, there are also two other theories used in assessing environmental satisfaction including the bottom-up theory and top-down theory. Bottom up theory considers overall satisfaction as a function of many aspects from physical, spatial, and social, each aspect is broken down into constructs and has different weights depending on the context and settings. The more consistent the above aspects are with the individual's core values, the greater the satisfaction (Li et al 2014, Mohi 2015). For example, some people value the role of relaxation and will be more satisfied when their place of residence has conditions that serve this value. The others who prioritize the health of themselves and their families the most will be satisfied when their living place giving priority to health aspects.
Top-down theory views satisfaction as the result of personal characteristics that are more long-term and stable. In that sense, satisfaction is determined by stable and core values of the individual such as affection, respect or social class.The top down effect can influence the perception of many aspects of satisfaction. From there, personal characteristics should be viewed as independent variables and explanations for satisfaction, rather than being viewed as control variables. Some empirical studies have proven this statement relatively clearly. Some other studies have found a mixed relationship between the above two aspects of personal characteristics (Luo and Timothy 2017, Hoogerbrugge and Burger 2018, Gui et al 2021).
2.2. Model development
Based on theories about environmental satisfaction, many empirical studies have been conducted in countries around the world to identify influencing factors, test theories and provide management implications. Basically, factors affecting individual environmental satisfaction are divided into 4 main groups including housing, public services and facilities, social networks and behaviors, socio-economics characteristics (figure 2).
Figure 2. Factors affecting environmental satisfaction in literature. Source: Compilation from literature (2023).
Download figure:
Standard image High-resolution image2.2.1. Housing factors
These factors are easy to identify, tangible and can be divided into two smaller groups: internal factors and external factors (Morris and Winter 1975, Fernandes and Costa 2018). Internal factors include area, layout, construction quality, garden, and entertainment area. Mohit and Manfound found a relationship between internal housing factors and satisfaction in Malaysia, proving that increasing house area leads to increased satisfaction. Other studies in developing countries also demonstrate similar propositions (Ahmad et al 2015, Akpinar 2016, Dai and Zhao 2020). For example, Dang et al (2021) showed that the more utility areas in the house increase households' satisfaction in China, Hoogerbrugge and Burger (2018) also found that kitchen and laundry area also positively impact residents' satisfaction in the Netherland. External factors include electricity, water, garbage collection, sewers, street lights, etc. These factors also impact individual satisfaction. For example, in Mumbai, the cleanliness of internal roads and the frequency of household garbage collection have a positive influence on resident satisfaction (Johnson and Chakravarty 2013).
2.2.2. Public service and facility factors
Amenity features have a significant impact on residents' environmental satisfaction. In particular, important utility factors identified are the presence of schools, medical facilities, supermarkets, convenience stores, gas stations as well as the distance from the residence to these facilities (Cai and Lu 2015, Dai and Zhao 2020, Gui et al 2021). Other non-physical factors include security, safety, and the risk of accidents. Accessibility to the public transportation, community facilities and physical environment variables were shown as critical factors of satisfactions (Calmeiro et al 2018, Dang et al 2021, He and Ahmed 2022). Also, Ibem and Amole (2013) showed that safety from accidents is a considered housing satisfaction factor. This is supported by other research which states that crime levels or lack of amenities, industrial development or workplace can be a contributing cause of neighborhood dissatisfaction (Salleh 2008, Mohi 2015, Le et al 2020). Therefore, it is implied that residential satisfaction not only depends on the housing factors but also neighborhood factors.
2.2.3. Social and behavioral factors
Social networks are a predictor of residential environmental satisfaction (Manzo and Perkins 2006, Li et al 2014, Luo and Timothy 2017). People not only live in homes but also have relationships and interactions with society. Social relationships originating from the place of residence play an important role in people's emotions and attachment to their place (Huang and Du 2015, Makinde 2015). Even in some developing countries, social relationships in the living community have a higher impact on emotions and environmental satisfaction than other social relationships such as professional relationships, friends or business (Bruin and Cook 1997, Austin et al 2002, Dinc et al 2014). In general, attributes including relations with neighbors and social relationships within the community are significant contributors to residential satisfaction. On the contrary, lack of community involvement in the neighborhood is the important predictors of dissatisfaction (Demirbatır et al 2013, Dong et al 2020)
In the case of resettlement, behavioral characteristics of residents or 'Housing adjustment and adaptation' are the family's effort to address the discrepancies between the housing it has and the housing had (Su et al 2009). Housing adjustment is a process that may occur when a family experiences a normative deficit that causes a significant reduction in satisfaction. It is also pointed out that behavioral characteristics of the residents reflect their feelings about their residential satisfaction and dissatisfaction (Wang and Wang 2016, Tong et al 2019). The residents react differently with their housing dissatisfaction. They may be adapted with the situation of their housing unit, or they may be done some modification at the certain part of their housing unit. It is all depends on the level of their dissatisfaction or the ability of relocation. The new attribute has been included in a study which is owners' culture of maintenance. It was found that this attribute to be significant together with existing residential attributes. Significant of attributes in the study according to the rank is starting with building quality feature and followed by owners' culture maintenance, social feature, neighborhood feature, management feature and dwelling unit feature.
2.2.4. Socio- economic characteristic factors
In addition to the above three factors, socio-economic characteristics are also related to individual environmental satisfaction (Teck 2012, Ibem and Alagbe 2015, Luo and Timothy 2017). Some important factors include gender, age, education, length of residence, income, and occupational status (Gui et al 2021, He and Ahmed 2022). As to Huang and Du (2015), men are more satisfied with the environment than women. Through the intermediary variable social network, men have more interaction with the community and society than women in China, from which they have higher satisfaction with the environment. Ibem and Amole (2013) also found a positive relationship between age and satisfaction while Mohi (2015) found the opposite relationship. Some other studies have found that individuals who own homes have higher satisfaction than individuals who rent, also due to more stable and long-term interactions with the social network at home. Income and education level are also positively related to satisfaction, along with local career opportunities in Malaysia, West Bengal and China. People with more opportunities will have higher satisfaction (Salleh 2008, Li et al 2014, Roy 2014) (table 1).
Table 1. Summary of some factors affecting environmental satisfaction.
| No. | Factors | Examples | Authors | Region |
|---|---|---|---|---|
| 1 | Housing factors | •Size of land | Johnson and Chakravarty (2013), Ahmad et al (2015), Akpinar (2016), Hoogerbrugge and Burger (2018), Dai and Zhao (2020), Dang et al (2021) | Thailand |
| •Toilet, kitchen | ||||
| •Elevator, stairs | ||||
| •Electricity | ||||
| •Water supply | ||||
| •Garbage collection | ||||
| 2 | Public service and facility factors | •School | Ibem and Amole (2013), Cai and Lu (2015), Mohi (2015), Calmeiro et al (2018), Dai and Zhao (2020), Gui et al (2021), Dang et al (2021), He and Ahmed (2022). | China |
| •Culture | ||||
| •Clinics | ||||
| •Markets | ||||
| •Bus stop | ||||
| •Bank | ||||
| •Parking | ||||
| •Sewers and sanitation | ||||
| •Distance to amenities | ||||
| •Traffic light | ||||
| 3 | Social and behavioral factors | •Civic organizations | Bruin and Cook (1997), Austin et al (2002), Manzo and Perkins (2006), Demirbatır et al (2013), Dinc et al (2014), Li et al (2014), Makinde (2015), Huang and Du (2015), Wang (2016), Luo and Timothy (2017), Wang and Tong et al (2019), Dong et al (2020). | Pakistan |
| •Neighbor | ||||
| •Internal online social network | ||||
| •Local information channels | ||||
| •Participate in local activities | ||||
| •Convenient in responding to comments | ||||
| •Local support | ||||
| •Local government | ||||
| 4 | Individual socio-economic characteristic factors | •Age | Salleh (2008), Teck (2012), Roy (2014), Li et al (2014), Ibem and Alagbe (2015), Huang and Du (2015), Mohi (2015), Luo and Timothy (2017). | India |
| •Gender | ||||
| •Education | ||||
| •Time of residency | ||||
| •Land ownership | ||||
| •Job opportunity | ||||
This study inherits the theoretical model of Shin (2016) and the results of empirical studies in developing countries to build a model to estimate factors affecting environmental satisfaction after land acquisition and resettlement of residents in Hai Phong city, Vietnam. Shin's theory emphasizes two main groups of structures that affect satisfaction: physical and social structures. At the same time, these structures are divided into layers and organized into interrelated networks from the level of households, neighbors, communities to ecosystems (natural and social). The study divided expected factors affecting people's environmental satisfaction after land acquisition and resettlement into 7 main groups including: (i) employment and job, (ii) income, (iii)) public services and facilities, (iv) environment, (v) health risk, (vi) local government and (vii) social networks. In addition to the above factors, the interviewer's personal characteristics are also assumed to have an impact on environmental satisfaction, and are classified as external factors like studies by Lai (2011), Huang and Du (2015), Ibem and Alagbe (2015) (figure 3).
Figure 3. Proposed research model for assessing impact factors of residents' environmental satisfaction. Source: Study design (2023).
Download figure:
Standard image High-resolution image3. Methodology
3.1. Overview of Hai Phong city, land acquisition and resettlement
Located about 120 km east of Hanoi capital, Hai Phong is not only the largest coastal city in the Northern region of Vietnam but also one of the major economic centers of the country. Hai Phong is among the five centrally run cities of Vietnam, along with Hanoi, Ho Chi Minh City, Can Tho and Da Nang. With an area of 1,527 square kilometers and a total population of 2.07 million in 2021, it is the seventh most populous city in the country. Located in a strategic location of the Red River Delta, Hai Phong serves as a major trading hub. It is the only city in the North with 5 modes of transportation including rail, road, air, inland waterway and maritime (figure 4).
Figure 4. Study area—Hai Phong city, Vietnam. Source: Study design (2023).
Download figure:
Standard image High-resolution imageIn recent years, Hai Phong has always maintained its position in the top two localities with the fastest growing gross regional product (GRDP) in Vietnam. Hai Phong's average annual growth rate in the period 2017–2021 is 15.26%, nearly double that of the period 2012–2016 and 2.9 times higher than the national average. In 2021, Hai Phong ranks first in the country in GRDP growth rate, reaching approximately 13.58 billion USD (Hai Phong People Committee 2021).
Along with economic development, urbanization also occurred rapidly in the period 2000–2020. The city center area has been embellished, upgraded, forming many new urban areas such as: Vinhomes Imperia, Hoang Huy, Agape, some 5-star hotels, AeonMall. Expanded public welfare works, built a number of new hospitals and schools; renovate and expand Tam Bac river; some green parks. Industry is also one of the three economic pillars that contribute most importantly to the city's development. The index of industrial production (IIP) increases by an average of 20.64%/year in the period 2016–2023, 2.12 times higher than the period 2010–2015 and more than twice the overall growth rate of the country. Hai Phong International Seaport has put into operation two launch berths, capable of receiving ships with a tonnage of 200 thousand tons. Industrial parks are also developing on a large scale such as Vinfast Industrial Park, Nam Cau Kien, VSIP, and Vu Yen Island (Hai Phong People Committee 2021).
With the rapid pace of urbanization and industrial development, in the period 2010–2020, Hai Phong has conducted 20 land acquisition and resettlement projects with the number of households in the resettlement area being 8,345 households. According to the provisions of the Land Law (2013), the State recovers land for purposes of national defense, security, national interests, public interests, and economic development. Based on the Land Law, Hai Phong City People's Committee has issued detailed regulations on land acquisition, compensation and resettlement in 2014 (Decision No. 2680/2014/QD-UBND). According to Government of Vietnam (2014), land acquisition is supported with land compensation, resettlement support, and livelihood support. During the period 2010–2023, Hai Phong has been building 15 resettlement areas with areas ranging from 10 hectares to hundreds of hectares to serve resettlement work (Hai Phong People Committee 2021). Resettlement areas are built on the outskirts of the city, where land funds have been planned to build urban areas with enough amenities. Households receive plots of land or apartments in resettlement areas. Here, planned roads include 5.5 m – 7.5 m – 10.5 m roads, convenient for moving around within the area. Surveillance cameras are installed at intersection corners to ensure security. Some settlements also build regulating lakes to bring water from the river to create fresh air for residential areas as well as avoid flooding during the rainy season.
3.2. Data collection and analysis
This study was reviewed and approved under the ethical approval document No. CBQT.30. 2023 by the Scientific and Trainning Committee of the National Economics University, Vietnam which has the responsibility of academic ethics approval of univesrity studies.
In this study, we divided data collection into three steps. In step 1, the study carried out 2 focus group discussions (FGD) with residents and a local government meeting to preliminarily identify factors affecting people's environmental satisfaction and use information collected from FGDs to build survey questionnaire. In the first FGD, people were presented with 4 groups of factors grouped in the literature in part 2 and developed constructs for each factor. For example, the utility factor of a residential area is divided into 7 constructs such as schools, medical centers, bus stations, banks, markets and waste treatment facilities. During this FDG, people also expressed their opinions on satisfaction or dissatisfaction with aspects of the land acquisition and resettlement process, such as the amount of compensation, the amount of relocation support, state policies to support careers or livelihood transformation.
The second FGD was conducted with 6 local management officials related to land acquisition and resettlement (Department of Natural Resources and Environment, Department of Construction, Department of Agriculture and Rural Development, Department of Transport, District People's Committees and Local Policy Bank). This FGD is a forum for managers to discuss land acquisition and resettlement policies, describe the land acquisition process, and challenges in the land acquisition and resettlement process. Members of this meeting also expressed their views on factors that can affect people's environmental satisfaction from the perspective of management and policy implementation.
In step 2, the survey questionnaire is designed and tested. The draft questionnaire includes 3 main parts: (i) socio-economic information of the people, (ii) attitudes about land acquisition and resettlement, (iii) assessment of factors affecting environmental satisfaction such as amenities, social relations, and government care and support. The questionnaire was tested with 20 randomly selected households in 3 resettlement areas to adjust and complete before the official survey. In the pilot survey, we collected people's feedback on how to be interviewed, how to ask questions, the order of questions as well as strategies for approaching respondents.
In step 3, official surveys were conducted in settlements in Hai Phong. The study used the following formula to estimate the sample size (Peterson 1994):
In which n is the sample size, N is the total number of households in population, e is accepted errors.
With 5% errors, and an overall population of 8,345 resettled households between 2010 and 2020, the calculated sample to ensure reliability is 550. The study used stratified sampling method to approach the respondents. We first selected 3 settlements (An Son, Kien Bai and Gia Minh) containing residents from 3 typical land acquisition projects of the city: (i) Nam Cau Kien industrial park construction project (ii) Trang Due industrial park construction project, (iii) highway renovation and construction project. Information on these settlements was collected from the second FGD. In each settlement, the researcher collected a list of households from the management board, and then randomly selected 195 households from interviews. In fact, 585 households in 3 resettlement areas participated in the investigation. Interviews were conducted in the evening when the head of household was most likely to be present. The investigation team approached households at home and introduced the purpose of the interview, information confidentiality and asked if they agreed to participate. If they agree, they ticked the agree option in each interview panel. If a household was absent, the next household was selected.
In the questionnaire, we combine the results of the first FGD and literature to build h specific statements for constructs and factors. The scales use the Likert form of 5 levels from 'strongly disagree' (point = 1) to 'strongly agree' (point = 5). There were 7 factors and 36 constructs for dependent variables, 1 factor and 3 constructs for independent variable (table 2).
Table 2. Questions for measuring variables in study model.
| No. | Factors and constructs | Code |
|---|---|---|
| EMPLOYMENT AND JOB (EPJ) | ||
| 1. | The jobs of family members have changed positively after acquisition | EPJ1 |
| 2. | Many opportunities for family members to find jobs after acquisition | EPJ2 |
| 3. | Many opportunities for women to find job locally in the new place | EPJ3 |
| INCOME (INC) | ||
| 4. | The family's current income is stable | INC1 |
| 5. | Family income is now increasing after acquisition | INC2 |
| 6. | There are many opportunities to find and increase income locally in new place | INC3 |
| PUBLIC SERVICES AND FACILITIES (PSF) | ||
| 7. | Current local commercial amenity system (markets, supermarkets, etc) meets the residents' needs | PEF1 |
| 8. | Current local environmental sanitation service system (waste collection and treatment) is good. | PEF2 |
| 9. | Current local medical and health care service system are good. | PEF3 |
| 10. | Current local education and vocational training services are good | PEF4 |
| 11. | Current local parking area, gas station and transport station are good | PEF5 |
| 12. | Current local legal assistance services are good | PEF6 |
| 13. | Current local banking is accessible and good | PEF7 |
| 14. | Entertainment services (amusement area, football field, etc) meet the residents' needs | PEF8 |
| ENVIRONMENT (ENV) | ||
| 15. | The air is polluted by dust and odors in the new area | ENV1 |
| 16. | Domestic water sources are seriously polluted in the new area | ENV2 |
| 17. | Land is polluted due to waste and garbage in the new area | ENV3 |
| 18. | Noise is polluted in the new area | ENV4 |
| 19. | The local landscape and environment are increasingly deteriorating, and pollution is becoming more and more serious | ENV5 |
| HEALTH RISK (HER) | ||
| 20. | Dust pollution in the new area affect people's health | HER1 |
| 21. | Domestic water pollution in the new area affects people's health | HER2 |
| 22. | Pollution of garbage, waste, and wastewater from industrial parks in the new area affect people's health | HER3 |
| 23. | The likelihood of getting diseases (respiratory problems, headaches, skin diseases, etc) is increasing | HER4 |
| SOCIAL NETWORK (SON) | ||
| 24. | Civic organizations in new area are developed and active | SON1 |
| 25. | I have better relations with neighbors in new area | SON2 |
| 26. | The information exchange with local social networks in new area are good | SON3 |
| 27. | My family feedbacks and contribution are well received in new area | SON4 |
| 28. | Current local legal assistance services are good | SON5 |
| LOCAL GOVERNMENT (GOV) | ||
| 29 | The local government operates effectively | GOV1 |
| 30 | The local government concern about job and income of residents | GOV2 |
| 31 | Local government is supportive in stabilizing people's lives after land acquisition and resettlement | GOV3 |
| 32 | Local government concerns about problems of environmental pollution, social evils, security, and others | GOV4 |
| 33 | Local government pay attention to the community's basic needs (electricity, water, roads, schools, healthcare, etc) | GOV5 |
| 34 | Local government provides complete and timely policy information to residents. | GOV6 |
| 35 | Local government pays attention and support in local training and career change orientation for the community. | GOV7 |
| 36 | Local government 's decision-making involves the participation of residents and communities | GOV8 |
| ENVIRONMENTALSATISFACTION EXTENT (ESE) | ||
| 1 | My family is satisfied with the housing factors in the new settlement | ESE1 |
| 2 | My family is satisfied with the public amenities in the new ESEttlement | ESE2 |
| 3 | My family is satisfied with the social networks in the new ESEttlement | ESE3 |
The model estimating impacting factors of households' environmental satisfaction in combination with socio-economic characteristics of respondents is specified as follows (table 3):
intercept
Table 3. Variables in estimated model and expected sign.
| Variables | Symbol | Scale | Expected sign |
|---|---|---|---|
| Environmental satisfaction extent | ESE | From 0 to 5 point | |
| Employment and job | EPJ | From 0 to 5 point | + |
| Income | INC | From 0 to 5 point | + |
| Public services and facilities | PSF | From 0 to 5 point | + |
| Environment | ENV | From 0 to 5 point | — |
| Health risk | HER | From 0 to 5 point | — |
| Social networks | SON | From 0 to 5 point | + |
| Local government | GOV | From 0 to 5 point | + |
| Gender | GENDER | = 1 male; = 0 female | + |
| Age | AGE | Age of respondents | — |
| Education level | EDU | Number of years of schooling of respondents | + |
coefficiences of influence factors
errors
SPSS 23.0 software was used for quantitative analysis in this research. SPSS showed the statistical description of variables, synthesize data on the frequency, and their effect on the environmental satisfaction of respondents. Besides, Cronbach Alpha technique was employed to test the reliability of study factors. Moreover, exploratory factor analysis (EFA) was implemented to eliminated unsuitable construct and grouping constructs into main factors. Multiple regressions then were carried out to examine the linear relations between dependent and independent variables.
4. Results
4.1. Characteristics of surveyed households
In the interview, 71.62% of respondents were male and 28.38% were female. Female-headed appliances included only 28.38%, this ratio is different because men act as heads of households more than women in Vietnam. Regarding age distribution, household heads between 30 and 40 represent 5.64%, those between 40 and 50 constitute 26.15%, and individuals aged 50 to 60 comprise 31.79%. Furthermore, households headed by individuals over 60 account for 36.41%. These figures indicate that most household heads are above 40 years old, totaling 94.36%. This shows that age significantly impacts local employment (older people find it more challenging to apply for jobs in companies in industrial zones), especially households whose land is recovered by the government. When receiving compensation and support after land acqusition, households must change their livelihoods and find new jobs. This significantly impacts farm household income and becomes a social security burden for local authorities (table 4).
Table 4. Characteristics of surveyed households.
| Characteristics | Number | Percentage |
|---|---|---|
| 1. Gender | ||
| Female | 166 | 28.38 |
| Male | 419 | 71.62 |
| 2. Age | ||
| 30–40 years old | 33 | 5.64 |
| 40–50 years old | 153 | 26.15 |
| 50–60 years old | 186 | 31.79 |
| Over 60 years old | 213 | 36.41 |
| Average age | 51 | — |
| 3. Education | ||
| Illiteracy | 18 | 3.08 |
| Elementary | 78 | 13.33 |
| Secondary | 201 | 34.36 |
| High school | 189 | 32.31 |
| Vocational training, college and postgraduate | 99 | 16.92 |
| 5. Average number of labors/household | ||
| Average number of laborers/households | 2.9 | — |
| Average number of male laborers /households | 1.5 | — |
| Average number of female laborers /households | 1.4 | — |
| 6. Monthly income of households (million VND) | 31.3 |
The educational level of households is also diverse. There are 18 illiterate breadwinners, accounting for 3.08%. Most breadwinners graduated from secondary school, accounting for 34.36%. 32.31% of breadwinners graduated high school. The percentage of household heads graduating from primary school is 13.33%. Household heads who completed vocational training, College, and Postgraduate education account for 16.92%. In general, the educational level in the study area mainly focuses on secondary and high school levels (accounting for 66.67%), with a low proportion of post-high school qualifications (16.92%). Low education is also an obstacle to the transition from agriculture to non-agricultural occupations that require high skills and expertise, causing many difficulties in learning a profession and difficulty in accessing other occupations and production and business activities in today's industrialized environment.
The average population per household is 4.2 people. The average male is 2 people/household, and the average female in each household is 2.2. The number of people in the family is the labor potential in the household, and the number of people participating in the household's production activities is the force that significantly contributes to the income of the farming household. The more workers participating in production and working in companies in industrial zones, the higher the household's income. The average number of primary laborers in a household is 2.9; male laborers are 1.5, and female laborers are 1.4 per household. Monthly household income is 31.3 million VND. This income level is not different from household income as data from Hai Phong Statistics Office (2022).
4.2. Residents' attitudes on acquisition and resettlement
4.2.1. Attitudes on employment and income
According to the occupational structure, before land acquisition, 70.77% of households worked in agriculture, 4.44% in business, 1.71% of workers, 3.25% of civil servants and state employees, and 3.25% of handicrafts. Industry and other employment sectors account for 17.09%, and non-professional occupations account for 2.74%. Research results show an significant change in career conversion after land acqusition. After land acqusition, some households no longer had land for agricultural production, a significant number switched to working as workers. The proportion of households doing production workers and business increased to 42.39% and 11.79% respectively. However, the number of state employees and officials reduced to 1.88%. However, the unemployment rate after acqusition increased because over-age workers (over 35 years old) were not accepted into companies in the industrial park. This also affects household income after acqusition and makes difficult for the government to solve job problems in resettlement areas (table 5).
Table 5. Employment before and after resettlement.
| Employment categories | Before resettlement | After resettlement | ||
|---|---|---|---|---|
| Number | % | Number | % | |
| Unemployed | 16 | 2.74 | 23 | 3.93 |
| Agriculture | 414 | 70.77 | 24 | 4.10 |
| Production workers | 10 | 1.71 | 248 | 42.39 |
| Business/trade | 26 | 4.44 | 69 | 11.79 |
| State employees and officials | 19 | 3.25 | 11 | 1.88 |
| Handicraft industry and others | 100 | 17.09 | 210 | 35.90 |
4.2.2. Attitudes on land compensation and supporting policy
Respondents expressed quite positive attitudes about state support in land acquisition and resettlement. Most believe that the government is proactive and supports them in compensating for recovered land and stabilizing a new life in the new resettlement area. 60.5% said the government's employment support policy is good, similarly the livelihood transformation training support policy was also rated as good by 55.7%. However, up to 68.7% of people think that the compensation policy for recovered land is not satisfactory, and that the State needs to refer more closely to market prices to establish a land compensation price framework for each specific location and closer to the actual situation. Although the credit policy to support life stabilization is considered as good by 45.2%, people still want more credit incentives such as lower interest rates because when changing their livelihood, investment costs are relatively large and for poor households, credit capital is very limited, requiring more attention from the government. Similarly, financial support for resettlement should also be reviewed and improved by the government because real costs are increasing rapidly due to inflation.
The expenditure of compensation money of households is fairly similar. Through investigation, almost compensation fund are used for daily living, house construction and shopping, with very little investment in production and education. However, there are also a significant number of households that have focused on investing in non-agricultural production or small business services, which are households whose main workers are middle-aged workers. For older workers, they tend to deposit money in credit institutions. The majority of households using money for shopping or construction are young households. Besides, some people reported to invest not only in material production but also in education and vocational training to stabilize their jobs and find more suitable jobs in the future (figure 5).
Figure 5. Use of compensation and support by households. Source: Study results (2023).
Download figure:
Standard image High-resolution image4.2.3. Attitudes about public services and facilities in the resettlement areas
According to assessments, the resettlement areas all have relatively good basic infrastructure such as electricity, schools, medical centers, water supply systems, street lights favorable conditions for residents to live. However, when moving people in, there was still unfinished construction such as roads, drainage systems, and markets. Some people also complain that when roads and houses are being built, there are many vehicles transporting materials back and forth while there are still no trees, causing dust. The drainage system is not complete and floods when it rains heavily, the drainage speed is slow. The road system around the resettlement area is mostly narrow. This not only limits daily life but is also an obstacle for those who want to do business. Infrastructure serving cultural and social activities, although planned early, is often built later than other projects. In addition, bus stations are located far from residential areas and are not convenient for using public transportation (figure 6).
Figure 6. Attitudes about public services and facilities in the resettlement areas. Source: Study results (2023).
Download figure:
Standard image High-resolution image4.3. Cronbach's alpha analysis
To ensure the scale's reliability, Cronbach's Alpha analysiss was employed. Constructs with a Cronbach's Alpha belowing 0.6 or Corrected Item-total Correlation belowing 0.3 are considered as invalid and removed (Peterson 1994). The analysis results showed all Cronbach's Alpha coefficients ranging from 0.601 to 0.932 for proposed factors, hence affirming their high reliability. Among the 39 observed constructs, PSF6, PSF7 and PSF8 exhibit correlation coefficients below 0.3, and each construct's Cronbach's Alpha exceeds that of the factor, they were thus removed. The remaining variables are retained for analysis for subsequent EFA (table 6):
Table 6. Cronbach Alpha analysis results.
| No. | Code | Corrected Item-total Correlation | Cronbach's Alpha if item deleted |
|---|---|---|---|
| Cronbach's Alpha = 0.848 | |||
| 1. | EPJ1 | 0.633 | 0.733 |
| 2. | EPJ2 | 0.760 | 0.801 |
| 3. | EPJ3 | 0.712 | 0.776 |
| Cronbach's Alpha = 0.742 | |||
| 4. | INC1 | 0.632 | 0.701 |
| 5. | INC2 | 0.653 | 0.679 |
| 6. | INC3 | 0.678 | 0.665 |
| Cronbach's Alpha = 0.673 | |||
| 7. | PSF1 | 0.654 | 0.625 |
| 8. | PSF2 | 0.642 | 0.623 |
| 9. | PSF3 | 0.603 | 0.601 |
| 10. | PSF4 | 0.599 | 0.663 |
| 11. | PSF5 | 0.544 | 0.698 |
| 12. | PSF6 | 0.232 | 0.679 |
| 13. | PSF7 | 0.254 | 0.682 |
| 14. | PSF8 | 0.282 | 0.692 |
| Cronbach's Alpha = 0.899 | |||
| 15. | ENV1 | 0.654 | 0.803 |
| 16. | ENV2 | 0.795 | 0.742 |
| 17. | ENV3 | 0.864 | 0.699 |
| 18. | ENV4 | 0.812 | 0.753 |
| 19. | ENV5 | 0.769 | 0.789 |
| Cronbach's Alpha = 0.932 | |||
| 20. | HER1 | 0.843 | 0.778 |
| 21. | HER2 | 0.834 | 0.782 |
| 22. | HER3 | 0.901 | 0.832 |
| 23. | HER4 | 0.893 | 0.865 |
| Cronbach's Alpha = 0.847 | |||
| 24. | SON1 | 0.534 | 0.653 |
| 25. | SON2 | 0.765 | 0.753 |
| 26. | SON3 | 0.604 | 0.756 |
| 27. | SON4 | 0.785 | 0.809 |
| 28. | SON5 | 0.821 | 0.812 |
| Cronbach's Alpha = 0.789 | |||
| 29. | GOV1 | 0.432 | 0.677 |
| 30. | GOV2 | 0.532 | 0.758 |
| 31. | GOV3 | 0.643 | 0.743 |
| 32 | GOV4 | 0.693 | 0.732 |
| 33. | GOV5 | 0.495 | 0.642 |
| 34. | GOV6 | 0.783 | 0.684 |
| 35. | GOV7 | 0.743 | 0.689 |
| 36. | GOV8 | 0.632 | 0.692 |
| Cronbach's Alpha = 0.901 | |||
| 37. | SE1 | 0.643 | 0.732 |
| 38. | SE2 | 0.783 | 0.821 |
| 39. | SE3 | 0.802 | 0.842 |
4.4. Exploratory factor analysis (EFA)
EFA was conducted on 36 observed variables belonging to 7 independent factors and 1 dependent factor. The Kaiser-Meyer-Olkin (KMO) was 0.801 (> 0.5), and the Bartlett's had a significant value of Sig = 0.00, indicating the appropriate of EFA model. The analysis revealed that at Eigenvalues > = 1 and 6 factors were extracted from the 31 observed constructs (after taking out 5 bad constructs) accounting for an extracted variance of 71.023% (table 7).
Table 7. Factor rotation matrix in EFA.
| Observed constructs | Factors | |||||
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | 6 | |
| HER3 | 0.908 | |||||
| HER2 | 0.889 | |||||
| ENV3 | 0.865 | |||||
| ENV2 | 0.842 | |||||
| HER4 | 0.817 | |||||
| ENV5 | 0.794 | |||||
| HER1 | 0.776 | |||||
| ENV1 | 0.739 | |||||
| ENV4 | 0.704 | |||||
| EPJ2 | 0.839 | |||||
| EPJ3 | 0.814 | |||||
| EPJ1 | 0.777 | |||||
| INC2 | 0.743 | |||||
| INC3 | 0.708 | |||||
| INC1 | 0.699 | |||||
| GOV5 | 0.901 | |||||
| GOV6 | 0.893 | |||||
| GOV4 | 0.874 | |||||
| GOV7 | 0.821 | |||||
| SON5 | 0.883 | |||||
| SON2 | 0.870 | |||||
| SON3 | 0.793 | |||||
| SON1 | 0.756 | |||||
| SON4 | 0.744 | |||||
| PSF5 | 0.885 | |||||
| PSF3 | 0.844 | |||||
| PSF1 | 0.797 | |||||
| PSF4 | 0.752 | |||||
| PSF2 | 0.714 | |||||
| ESE2 | 0.852 | |||||
| ESE1 | 0.824 | |||||
| ESE3 | 0.976 | |||||
| Variance extract | 71.023% > 50% | |||||
| KMO | 0.5 < 0.801 <1 | |||||
| Significance level of Bartlett's test | 0.000 < 0.05 | |||||
New factors have disturbances in observed variables after rotating factors:
- Factor F1 is formed from variables HER3, HER2, ENV3, ENV2, HER4, ENV5, HER1, ENV1, ENV4. This factor had new name 'Environment and health' (EAH)
- Factor F2 is formed from variables EPJ2, EPJ3, EPJ1, NC2, INC3, INC1. This factor had new name 'Employment and income' (EAI)
- Factor F3 is formed from the variables GOV5, GOV6, GOV4, GOV7. This factor kept former name 'Local government' (GOV)
- Factor F4 is formed from variables SON5, SON2, SON3, SO1, SON4. This factor kept former name 'Social networks' (SON)
- Factor F5 is formed from variables PSF5, PSF3, PSF1, PSF4, PSF2. This factor kept former name 'Public services and facilities' (PFS)
- Factor F6 is formed from variables ESE2, ESE1, ESE3 and kept former name 'Environmental satisfaction extent' (ESE).
The proposed research model is hence adjusted accordingly as follows:
intercept
coefficiences of influence factors
errors
4.5. Multivariate regression analysis
The multivariate regression analysis yielded adjusted R2 = 0.673, indicating that 67.3% of the variance in environmental satisfaction can be attributed to 5 included independent variables. The model fit test confirms the model's suitability with a significance level (Sig) of 0.00. Additionally, there is no evidence of multicollinearity, as all variables have variance inflation factors (VIF) below 2.0. The results showed 6 factors in the model having significant impacts on households' environmental satisfaction after land acquisition (p value <0.05). They are environment and health, employment and income, local government, social networks, public services and facilities, education. The variable with the strongest impact on satisfaction is 'Employment and income' and the variable with the weakest impact is 'Education' (table 8).
Table 8. Regression analysis results.
| Independent variables | Unstandardized coefficients | Standardized coefficients | T value | Sig. | Collinearity | ||
|---|---|---|---|---|---|---|---|
| B | Standard error | Beta | Tolerance | VIF | |||
| Constant | 0.370 | 0.215 | −1.087 | 0.256 | |||
| EAH | 0.013 | 0.056 | 0.111 | 0.349 | 0.027** | 0.954 | 1.786 |
| EAI | 0.267 | 0.057 | 0.221 | 8.535 | 0.012** | 0.905 | 1.340 |
| GOV | 0.193 | 0.058 | 0.187 | 4.996 | 0.000*** | 0.876 | 1.574 |
| SON | 0.154 | 0.057 | 0.142 | 3.803 | 0.033** | 0.907 | 1.837 |
| PSF | 0.179 | 0.056 | 0.168 | 6.035 | 0.000*** | 0.948 | 1.193 |
| Age | 0.235 | 0.006 | 0.119 | 1.978 | 0.242 | 0.883 | 1.066 |
| Gender | −0.267 | 0.133 | −0.118 | −1.945 | 0.086 | 0.858 | 1.296 |
| Education | 0.086 | 0.019 | 0.073 | 0.588 | 0.031** | 0.807 | 1.166 |
| Adjusted R2 | 0.673 | ||||||
| Pr> χ2 | 0.000 | ||||||
*** significant at 10% level, ** significant at 5% level Source: Study results (2023)
The standardized equation for factors affecting environmental satisfaction is:
5. Discussions
The study analyzed and showed factors affecting people's environmental satisfaction after land acquisition and resettlement in Hai Phong city, Vietnam with 6 main impact factors identified.
Firstly, the factor 'Employment and income' (EAI) has the strongest and positive impact on residents' environmental satisfaction. The positive impact is consistent with expectations, this is the factor that has the strongest influence on people's satisfaction and is similar to some empirical studies in developing countries such as Demirbatır et al (2013), Dinc et al (2014), Wang and Wang (2016), Tong et al (2019), and Dong et al (2020). Residents whose land is recovered are mostly agricultural households and poor households with low income. Their biggest concern is career and income to stabilize their family's life. Therefore, their satisfaction after resettlement depends largely on their occupation and income. Research showed that a large number of households have converted from agriculture to working as workers in industrial parks in Hai Phong. This led to a change in the main livelihood of the household and also resulted in higher income from industrial livelihoods. However, industrial parks often only prioritize recruiting male workers under 40 year old and female workers under 35 year old. This can make it difficult for elderly households to change their livelihoods. Many households have switched to alternative livelihoods such as retail trading, working as hired laborers or staying at home and are in need of transition support. Particularly for workers, they need skills support corresponding to the transforming industry. According to the investigation, support in Hai Phong still does not match the training and skills actually needed. Livelihood transformation, income and satisfaction are closely related; to solve this problem satisfactorily requires vision and synchronized policies of management agencies. This is also emphasized in studies about policies and mechanisms to create income and jobs for people after resettlement by Dinc et al (2014), Makinde (2015), Huang and Du (2015), Hoogerbrugge and Burger (2018). These papers indicated that resettlement that does not generate adequate income and jobs can cause social evils and community-level conflicts.
Secondly, the factor 'Local government' (GOV) has the second strongest and positive impact on households' environmental satisfaction. Local support is very important to help people stabilize their lives, convert to suitable livelihoods and create a basis for long-term life development. In this study, people are very interested in different aspects of support from the government. They not only appreciate the importance of income and employment support solutions but also appreciate the government's training, information and financial support. In general, land acquisition and resettlement create major changes in the lives of households and government assistance is essential to create a new, stable life. Of course there are many different aspects of support and not every locality or government has adequate support. In Hai Phong, people rate the government's role well in overall; however there are aspects they still rate poorly, such as attention to environmental quality and public services in the new settlement, or social evils arising when changing residence and livelihood. This result is similar to previous studies on the supporting role of government, for example Manzo and Perkins (2006), Li et al (2014), Makinde (2015), Luo and Timothy (2017).
Thirdly, the 'Public services and facilities' (PSF) has a positive impact on household satisfaction, similar to previous studies by Cai and Lu (2015), Dai and Zhao (2020), Gui et al (2021). However, survey results show that people do not have high satisfaction with this factor. The main reason is that the process of forming resettlement areas focuses more on building houses for people. Although infrastructure and utilities are included in the planning, they receive less investment and attention, leading to delays in construction and operation. This causes great inconvenience to residents because they not only live in the new house but also use the utility services of the residential area and community. In Hai Phong, people believe that basic services such as electricity and water are provided sufficiently but other facilities such as schools, hospitals, and sports playgrounds are not enough. This requires the role of the state and a synchronous investment with many resources and utility priorities that must be given equal attention in the settlement construction process. Similar to this result are studies by Ibem and Amole (2013), Mohi (2015), Calmeiro et al (2018), Dang et al (2021), He and Ahmed (2022).
Fourthly, besides public facilitiess, 'Social network' (SON) is also a factor that positively affects residents' satisfaction. Social networks are not only interactions between households and neighbors and communities, but also include interactions beyond the boundaries of the community and the connection of different networks to strengthen the family's social capital. In this study, people highly appreciate the role of local civic organizations such as the Women's Union, Veterans Association, Farmers Association or Youth Union in supporting and stabilizing livelihoods and life after resettled. They also promote the role of community information channels through social networks and traditional direct announcements. At the same time, emphasize the desire that family feedback must be recorded at the community level and implemented through grassroots social networks. In developing countries, social networks in the community include not only formal organizations but also informal networks. For example, community credit unions or neighborhood arts teams. Participating and interacting with such associations makes family life better, even safer, thereby increasing people's satisfaction with their new residential environment. These findings are also similar to the theoretical model of Shin (1996) and empirical studies such as Bruin and Cook (1997), Austin et al (2002), Manzo and Perkins (2006), Li et al (2014), Makinde (2015), Huang and Du (2015), Luo and Timothy (2017), and Tong et al (2019).
Fifthly, the factor 'Environment and health' (EAH) has the weakest impact on people's environmental satisfaction. As health risks and environmental pollution increase, satisfaction decreases, similar to the results of the studies by Teck (2012), Ibem and Alagbe (2015), and Luo and Timothy (2017). It is clear that environmental quality plays an important role in quality of life. However, in developing countries, environmental quality is still considered a secondary good; it only receives more attention when people have essential goods such as income, health care, and education. The results in Hai Phong also show similarities with studies in developing countries, that environmental quality and health risks have a significant impact but are not the strongest factors such as Huang and Du (2015), Wang and Wang (2016), Tong et al (2019). As income increases, this factor gradually becomes more important to satisfaction, as shown in studies by Demirbatır et al (2013), Wang and Wang (2016), Tong et al (2019), Dong et al (2020).
Finally, among the economic and social factors, only the educational level variable has a significant and positive impact on household satisfaction. Age and gender variables do not have a significant impact on satisfaction. This result is different from some previous studies such as Teck (2012), Ibem and Alagbe (2015), Luo and Timothy (2017) when pointing out the role and impact of age and gender variables on satisfaction. In Hai Phong and Vietnam, people of different genders and ages are involved in social processes and there is no great social distinction between men and women in career opportunities or social contributions, especially at the level of low and middle income groups. Therefore, the perception between men and women may not be significantly different in terms of environmental satisfaction when they are both involved in the process of land acquisition, compensation and resettlement. However, this study is similar to studies by Shalleh (2008), Roy (2014), and Li et al (2014) that as the level of education increases, the level of satisfaction of people increases. This is also consistent with Shin's (2016) environmental satisfaction theoretical model.
6. Conclusions
The research results have brought significant scientific and practical contributions in identifying factors affecting environmental satisfaction of households after land acquisition in Hai Phong City. We have identified 6 significant factors affecting environmental satisfaction including 'Employment and income', 'Local government' 'Public services and facilities', 'Social networks', 'Environmental and health' and 'Education'. The following implications are proposed from the results:
For employment and income: it is crucial to implement policies for vocational training and career transition assistance for households affected by land acquisition, especially targeting the youth labor force in the local area, aligning with the industries and professions recruited by the industrial zones. There should be preferential policies for vocational training for women and prioritized training and job placement for categories categorized as poor or near-poor. Credit financial institutions should provide favorable loan terms to support households reestablishing their livelihoods after land acquisition. Additionally, regulations should bind investors in land acquisition projects to prioritize hiring labor from households affected by land acquisition.
For public services and facilities: prioritize public services should be established to meet the daily consumer needs such as bus stations, entertainment, sports, and community cultural activities. To do this, planning needs to be done in detail, and at the same time the state needs to allocate an adequate budget to build public utilities synchronously and promptly to serve resettlement. Many public utility projects are delayed or not implemented as planned due to lack of capital, leading to inconvenience and dissatisfaction of people.
For local government support: people need a satisfactory compensation and resettlement support policy, so the government needs to design these policies based on actual situations such as market price of land, property valuation associated with land and resettlement costs. Local authorities must also address infrastructure issues, including electricity, clean water for domestic use, schools, healthcare facilities, and transportation networks. Additionally, efforts should be made to improve the environmental pollution situation in resettlement areas. Providing comprehensive information about policies to citizens is essential, and public infrastructure projects should involve discussions and consensus-building among the community for effective implementation.
For environmental and health: despite efforts, waste management and water pollution issues persist in the vicinity of resettlement areas. In addition to building environmental quality management projects such as garbage collection areas, sewers, and wastewater treatment areas, the government needs to establish and allocate spending for monitoring, environmental improvement, and treatment violation cases. Especially closely following the resettlement area planning and environmental impact assessment reports with environmental protection plans that have been reviewed and approved to ensure environmental quality for people's lives after land reclamation.
Acknowledgments
This research is funded by the National Economics University, Vietnam.
Data availability statement
All data that support the findings of this study are included within the article (and any supplementary files).
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.