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Social Capital and Migration: A Case Study of Rural Vietnam

  • Received : 2021.09.15
  • Accepted : 2021.12.01
  • Published : 2022.01.30

Abstract

To investigate the short-run effects of social capital on migration decisions of individuals in the rural areas of Vietnam, we conducted dataset mining and performed regression model analysis in the form of panel data. As control variables, we employed the variable of social capital, which is measured by an individual's network, as well as demographic characteristics of individuals and households. We discovered that when a household is in financial distress, social networks such as linkages or asking for aid from others often enhance individual capacity. Individuals with a large social network outside of their immediate area are more inclined to relocate to the location where their connectors live. Individual participation and degree of participation in the organizational community, on the other hand, have little bearing on the likelihood of migration. In addition, this research examines theories and empirical research on the relationship between social capital and migration. Based on our research findings, we have recommended some measures to boost the efficiency of social capital and migration in rural areas of Vietnam through local government solutions.

Keywords

1. Introduction

Internal migration has been seen as one of the driving forces behind the dramatic economic, political and demographic transformation of Vietnam over the past 25 years (Winkels, 2012). Chun and Sang (2012) have identified two main drivers of migration in Vietnam: (i) underemployment (stable), and (ii) low income in rural areas. At the same time, the National Migration Report (2016) also shows that the rural-urban migration flow accounts for the largest proportion among the internal migration flow, in which the social network of migrants plays an important role when one decides whether to migrate or not, especially from rural areas to large cities.

Members of the social network who play a critical role in migrating decisions are the source of information about job opportunities in the destination. Typically, these are relatives who lived and worked at the destination. According to the research, 46.7 percent of migrants learn about their current home through referrals from family or friends. Sixty-four percent of migrants stated they have relatives, friends, or countrymen in the destination.

Women account for a bigger percentage of the population than men. This is similar to empirical migration research that reveals that social media is a major factor of migration planning and destination choice (Palloni et al., 2001; Knack, 2002; Hotchkiss & Rupasingha, 2018). As a result, social network engagement has a major impact on migration decisions. Previous research has found that the stronger the social relationship, the higher the rate of migration (Massey et al., 1994; David et al., 2010; Curran et al., 2008; Garip, 2008). In addition, the impact of social capital on migration is not limited to family and local friends and establishes the relative importance of the multiple dimensions of social capital to migration decisions (Hotchkiss & Rupasingha, 2018). This evidence shows that social capital and migration are interrelated and to formulate the appropriate migration policies, a better understanding of this relationship is needed.

The contribution of migration to Vietnam’s socioeconomic development is significant and unavoidable. Migration provides an opportunity to foster inclusive, all-encompassing development while also reducing regional inequities. Migration moves money to poorer regions by satisfying the majority of labor demands created by the development of foreign-invested industries under Vietnam’s Doi Moi program. Assuring migrants’ rights and promoting migration’s effects to maximize the advantages to migrants, their families, and communities is a critical job for Vietnam’s future growth.

To provide empirical evidence for Vietnam’s migration policies in the coming time, the study wants to assess how the social capital’s people living in rural Vietnam affected the migration decision.

2. Literature Review

2.1. Social Capital Theory

There have been many different definitions and explanations of social capital due to different approaches in defining social capital (Baker, 1990; Bourdieu, 1986; Coleman, 1988; Fukuyama, 2002; Henn et al., 2005; Portes, 1998; Putnam et al., 1994; Putnam, 2000). According to Bourdieu (1986), Coleman (1988), and Putnam (2000), the concept of social capital is constructed as a multidimensional construct that includes awareness (i.e. mutual trust) as well as structural elements (social networks). Researches have increasingly focused on the context and perception of social capital through tools such as community trust (Putnam, 1995), neighbor support (Perkins et al., 2002), community cohesion (Perkins et al., 1996), life satisfaction (Prezza et al., 2001).

In general, social culture is defined based on three approaches:

First, social capital is associated with social networks and social relations. For example, social capital connected to social networks is relatively stable (Bourdieu, 1986), social capital belongs to social relations (Coleman, 1988), social capital belongs to social networks (Lin, 2001), social networks are a component of social capital (Putnam, 2000).

Second, individuals can use social capital to seek benefits by investing in social ties, or social networks and individuals can use social capital to seek benefits. According to Coleman (1988), social capital is created through interpersonal relationships. People form and sustain relationships for the purpose of making money. Individuals can generate and use social capital to serve their own objectives, according to Fukuyama (2002). Meanwhile, according to Putnam (2000), social capital is used to achieve economic or academic success.

Third, trust and reciprocity are mentioned by many authors when discussing social capital. The concept of social capital includes a norm of reciprocal relationships - based on recognized or known networks in which members interact and trust (Bourdieu, 1986; Coleman, 1988; Fukuyama, 2002; Portes, 1998; Putnam, 2000).

Varied dimensions of social capital can have different implications on economic and social outcomes such as education, economic development, health, and employment, as evidenced by the diversity of definitions and interpretations (Knack, 2002). Higher levels of social capital are linked to better academic performance (Hanifan, 1916), faster economic development (Knack & Keefer, 1997), more efficient economic development (Isham, 2002), lower crime rates (Akçomak & Weel, 2012; Buonanno et al., 2010), and more efficient government (Akçomak & Weel, 2012; Buonanno et al., 2010), and more efficient government (Boix & Posner, 1998).

2.2. Empirical Studies on The Relationship Between Social Capital and Migration

Social capital has been found to serve a positive effect in economic, social, and community growth in several studies across a variety of sectors. Different aspects of social capital can influence economic and social results in different ways (Knack, 2002). Several studies, in particular, have looked into the impact of certain aspects of social capital on migration decisions. The relationship between social capital and migration is emphasized in Putnam (1995), David et al. (2010), and Kan (2007). Social capital has been found to have a positive effect on economic, social, and community growth in several studies across a variety of sectors. Different aspects of social capital can influence economic and social results in different ways (Knack, 2002). Several studies, in particular, have looked into the impact of certain aspects of social capital on migration decisions (Deller et al., 2001; Graves & Linneman, 1979; Michaelides, 2011; Oehmke et al., 2007; Yao et al., 2016).

Granovetter (1973) used weak connection theory, which focuses on personal relationships, to examine the strength of social interactions in the job search of an individual. According to research, the following four criteria describe the quality or weakness of a relationship: time spent in the connection, emotional intensity, affection, and reciprocal services. As a result, members of a network with strong ties, such as family, relatives, friends, and coworkers, benefit from the ability to instantly share information within the network. Social capital, according to Adams (2006), is a network of’ mutual support’ or reciprocal exchange. As a result, during the migration process, networks can be considered the defining component of social capital.

2.3. Family and Relatives Relationship

Spilimbergo and Ubeda (2004) showed that family relationship is the reason for differences in migration decisions between ethnic groups. Kan (2007) argued that the interaction between friends and family members at the place of residence is a necessary source of help and brings positive effects such as a lower crime rate and a better physical environment. Kan (2007) suggested that people benefit materially and spiritually from local social interactions, focusing on local social relationships. Simultaneously, the study discovered evidence that people are hesitant to relocate because of their social capital. According to Kan (2007), geographical distance limits the benefits acquired. The author employs a query about local social capital information for the empirical study (for example, is there someone nearby who can spend more time helping in an emergency?).

To depict the relationship between social capital and local migration, David et al. (2010) developed a model with two possible equilibria. (as assessed by contact with friends, relatives, neighbors, and members of local organizations) and actual evidence to back up the idea. Individuals with stronger family links are less likely to relocate, according to Alesina and Giuliano (2011), Alesina et al. (2015), and Jung (2020). Palloni et al. (2001) examined information based on family networks to evaluate the relationship between social capital and international migration.

According to research, social capital among family members and households has a significant impact on migration. In their analysis of inequalities in migration rates between whites and blacks in the United States, Spilimbergo and Ubeda (2004) investigated familial ties as a factor determining migration. They discovered that blacks are less likely than whites to emigrate because blacks have greater familial ties. Only friendships and migration were studied by Belot and Ermisch (2009), who discovered that having three best friends living close and having the option to meet them frequently reduced the likelihood of persons migrating.

2.4. Community Involvement

Migration activities are also influenced by social capital in terms of community consciousness. According to McMillan and Chavis (1986), social capital is associated with a sense of belonging, a perception that members of a community are essential to one another, and a shared belief in commitment.

It’s only natural that a group of residents will form at least one community organization to collaborate on similar issues. Social ties, shared interests, and shared beliefs are all part of community involvement. According to Abadi et al. (2020), families with higher social capital can send their members to work as migrant workers for other families.

People’s social capital is strengthened when they belong to groups, associations, and participate in group activity clubs, according to pioneering social capital experts. Individuals engaged in communal activities, according to Putnam (1993), will develop habits of economic cooperation, solidarity, and collective spirit. Community participation, according to previous research, is a form of social capital that leads to increased social well-being. Potential migrants, according to David et al. (2010), see the community of groups and organizations as a positive component in their migrating process.

2.5. Political Activism and Participation

According to Cheong et al. (2007), the value of social capital varies depending on the social, economic, and political setting of migrants. There hasn’t been much research on the link between political participation and migrant social capital. Despite several obstacles, most migrants engage in political activity (Barreto & Munoz, 2003). In general, social capital has a positive influence on civic and political involvement for migrants; however, this effect varies depending on the country of origin and destination, as well as the type of participation (Lindstrom, 2005; Togeby, 2004; Santosa et al., 2020).

The differing relationship between social capital and civic and political participation in developing and developed countries, according to Palmer et al. (2011), can be attributable to two key conditions: adverse treatment and cultural differences. Social capital, for example, can help to organize community activities that promote local political participation (Putnam, 1993). People who are separated and alienated from social networks and the larger community, on the other hand, are more likely to disengage from political and social activity (Henn et al., 2005; Hoang & Truong, 2021).

2.6. Religion

Religion-related social interactions have a mixed effect on economic and social results. If they are related to migration, we will focus on this element in this post. Religious views were linked to economic development, such as per capita income and growth, according to Guiso et al. (2002). It is measured using variables such as church attendance, how frequently a person joins a religious organization, and whether or not they participate in a religious organization. The regularity with which a person participates in those activities can indicate how closely he or she is connected to the community. However, if they serve their own religion, religious activities at a high communal level may attract potential migrants. Predictions concerning the community’s general belief level are extremely difficult to make.

2.7. Urban-Rural Context Differences

Current research suggests that rural migrants differ from those who live in cities in terms of social capital. According to Putnam (1995), urban areas are less socially connected than small towns and rural areas. Furthermore, Glaeser et al. (2002) found that city dwellers are more likely to employ social capital. Both possibilities are presented by Hilber (2010): While urban areas foster greater social connections as a result of large population densities, certain regions foster a more anonymous environment, resulting in less social interactions.

2.8. Internal Migration in Vietnam

Over the last three decades, Viet Nam has seen a significant migration process. Since 1986, economic reform has boosted economic prospects and supplied the rural labor workforce ready to relocate to urban regions in search of jobs. This is fueling large-scale rural-to- urban migration movements in Vietnam. This is fuelling large migration flows from rural to urban in Vietnam. At the same time, the social network of migrants has further supported the migration process, especially migration from rural areas to big cities. The results of the internal migration survey showed that 79.1% of the migrants came from rural areas, the rest were migrants originating from urban areas. Considering the four migration flows (rural-urban, urban- rural, rural-rural, and urban-urban), rural-urban migration flow accounts for the largest proportion of the internal migration flows. Internal migration plays an important role in population change and has a close relationship with many issues of socio-economic development. According to the General Statistics Office (GSO) (2015), 13.6% of the country’s population are migrants. The proportion of migrants aged 15–59 is 17.3%, of which in-migrants account for 16.0%; Returning migrants and intermittent migrants make up insignificant. According to the research, 46.7 percent of migrants learn about their present location through referrals from relatives or friends, with women having a higher share than men. Few migrants acquire information about their origins through official sources such as employers and employment agencies, both of which are vital sources for migrants to be aware of. Approximately 64% of migrants claimed they have relatives, friends, or countrymen living in the destination.

3. Data and Methodology

3.1. Data

Our study draws on a cross-data sample from the Vietnam Access to Resources Household Survey 2016 (VARHS, 2016), which is conducted every two years by the General Statistics Office (GSO) in 12 provinces across Vietnam, including Ha Tay, Phu Tho, Lao Cai, Dien Bien, Lai Chau, Nghe An, Quang Nam, Khanh Hoa, Dak Lak, Dak Nong, Lam Dong, and Long An. The major goal of this survey is to collect extensive information to better understand the socioeconomic position of rural Vietnamese households, with an emphasis on access to and use of production resources such as physical, financial, human, and social capital. The survey, which has a sample size of 2, 669 homes and 10, 926 individuals, uses a stratified sampling method to collect data on migration, social capital, and demographic characteristics of individuals and households (age, gender, education, religion, land, income, etc).

3.2. Measurement of Migration Variables and Social Capital

We use a dummy variable to quantify migration in this study, which is equal to 1 if the individual has relocated from the locality in the recent 5 years and 0 otherwise. Then we assess an individual’s social capital by looking at their social network in the community, which includes both formal and informal networks. To be more specific, the formal social network will be defined by whether or not the individual engages in community groups, as well as the level of personal involvement in these organizations. Furthermore, political engagement is a channel of the formal social networks, which we evaluate by asking if a member of the family, a relative, or a friend works in a state agency at the local or central level (Stone et al., 2004; Wang et al., 2014; Thomas, 2015).

Personal interactions with relatives, friends, colleagues, and neighbors create an informal social network. In more depth, the variable of getting help from others is assessed using questions. “Does the household receive help from other people when they face financial difficulties?”; Number of helpers’ variable is measured by the question “How many people are willing to help your family?”. Similarly, the questions used to assess the Year know helper variable, the level of interaction variable, and the Living helper variable are “How long have you known this person?”, “The level of interaction between households and this person? and “Does this person live with the locality with you?” respectively (Cohen, 2004; Stone et al., 2004; Gottlieb & Bergen, 2010). Most variables representing social capital are either dummy variables or categorical variables. Furthermore, we assess social capital by determining whether or not an individual is a member of any form of group (Organizational participation variable) and how frequently to join. We also use the variable Political links to see if people are related to friends or relative who work in government offices. A variety of control variables on demographic characteristics of individuals and households, such as age, gender, educational level, religion, marital status, per capita income, the number of dependents in the home, and the land area owned by the household, were also included in the study.

3.3. Descriptive Statistics

The information in Table 1 pertains to variables. Our sample comprises 9,122 people who live in rural areas in Vietnam, half of whom are women, and 4.19 percent of whom have ever moved out of their homes. These people have an average age of 37 years, 77.6% have no education, and 57.7% are married. They live in homes with an average size of 5 persons, an average number of dependents of 2, an average cultivated area of 0.82 hectares, and an average per capita income of VND 27.5 million.

Table 1: Descriptive Statistics

OTGHEU_2022_v9n1_63_t0001.png 이미지

Every person in the sample participates in at least one community organization, with 63.7 percent of them doing so on a regular basis. Furthermore, the data sample shows that when a household suffers financial difficulties, an average of 5 persons is eager to assist, with 70% of those wanting to assist living in the same area as the household. Furthermore, relatives, relatives, and acquaintances work in state agencies in 7.36 percent, 16.15 percent, and 73.55 percent of households, respectively.

3.4. Estimation Methods

The main estimation method of this study is the logistic regression model. The authors assume the probability of migration of an individual as a function of social capital, personal and household characteristics as follows:

Migrationih = β0 + β1Social Capitalih + β4Xih + β5Hh + µih

in which represents migration status of the individual i of the household h, and it is a dummy variable indicating whether an individual has been migration for 5 years ago. Social capital includes some variables such as political links, the level of participation in organizations, the number of people who help when the household is having trouble, the number of years know this person, this person’s living place, and the level of interaction with this person. X covers individual characteristics such as age, gender, education, and marriage; H includes variables of household characteristics such as the total number of household members, the ratio of the dependents, the area of residential land, and per capita income. µ is the error term. The effects of social capital on the probability of migration of an individual are reflected in the estimated coefficients β1.

3.5. Research Hypothesis

Hypothesis 1: Individuals who have a large social network and receive financial or emotional benefits from it are less likely to migrate out of their communities, implying that strong family, friends, and neighbor relationships will have a negative impact on individual migration decisions because the opportunity cost for migration decisions is currently very high. Spilimbergo and Ubeda (2004), Kan (2007), David et al. (2010), and Alesina et al. (2015) all support this hypothesis.

Hypothesis 2: Individuals who are involved in community organizations frequently have contacts, economic cooperation, and information sharing with other members. They gain some advantages from involvement, such as lower transaction costs and more market options in production, credit, land, and labor (Narayan & Pritchett, 1999; Putnam et al., 1994). As a result, we hypothesize that participation in local community organizations reduces the likelihood of an individual migrating out of their locality. This hypothesis is supported by Hotchkiss and Rupasingha (2018).

4. Estimation Results

The model results in Table 2 reveal that social capital has an effect on the likelihood of persons living in rural Vietnam migrating. Hotchkiss (2018), Garip (2008), and Kindler et al. (2015) all came to the same conclusion. To be more specific, at the 1% level of significance, the chance of migration of individuals with friends working in state agencies is 1.86 percentage points higher than that of other individuals. Besides, when the number of helpers increases by one member, the probability of migration grows by 0.08 percentage points. The number of years spent knowing the helpers increased by one year, resulting in a 0.04 percentage point rise in the likelihood of household members migrating. At the ten percent significance level, the risk of individuals in families migrating increases by 0.94 percentage points if help dwells in different cities. The amount of engagement with volunteers or participation in community groups is not statistically significant. As a result, there is insufficient evidence to establish that the level of engagement with assistance and membership in community groups influences the likelihood of migration.

Table 2: Logit Regression Results for the Probability of Migration of Household Members

OTGHEU_2022_v9n1_63_t0002.png 이미지

*Significant at 10%; **Significant at 5%; ***Significant at 1%.

The probability of migration is also influenced by some control variables relating to individual and family characteristics. At a 1% significance level, the likelihood of persons leaving the locality decreases by 0.1 percentage point as their age increases by one. Marital status plays a role in migration decisions as well; married persons have a 3.91 percentage point higher chance of emigrating than single people. Furthermore, educational achievement increases an individual’s likelihood of migration, as shown in Table 2. Furthermore, increasing the number of dependents in a home by one reduces the likelihood of migration by 2.75 percentage points, whereas household income has no effect on migration preferences. Finally, as household sizes grow by one member, the likelihood of migrating increases by 0.41 percentage points. The above findings are in line with Grarip (2008).

Social capital has a significant impact on the migration behavior of persons living in rural parts of Vietnam, according to the research. The tendency of movement is from rural to urban regions, and it affects not just people in the family but also the entire household. This is due to reasons such as marriage, the relationship between members of the foreigner’s family, migration, and educational achievement and money. Workers have relocated to cities in search of higher wages and a better quality of life. This has increased the population density in urban areas; however, when they face life events such as epidemics, unemployment, etc., the workers tend to return to the countryside.

As a result, we believe that local governments from rural to urban areas need to create mechanisms and policies to expand employment opportunities and attract workers with suitable and diverse jobs for different levels to solve the problem of migration, especially after the covid-19 epidemic caused a shortage of migrant workers in big cities. At the same time, reasonable social security policies are required so that employees feel safe working and settling in the places where they migrate, limiting worker movement from one location to another and vice versa when changing residences, and limiting the societal loss caused by migration.

5. Conclusion

This study examines the impact of social capital on the likelihood of migration. When households are in financial distress, social networks such as political affiliations or getting support from others appear to enhance the likelihood of individual migration within the household. It is often easier for people from outside the locality to move to the locality to work if they have a large social network in their area of residence Individual migration is also influenced by household and individual characteristics. Individual participation and level of involvement in community groups, on the other hand, had no effect on migration decisions.

References

  1. Abadi, P., Otsuka, Y., Supriadi, S., & Olla, A. (2020). Probability of ionospheric plasma bubble occurrence as a function of prereversal enhancement deduced from ionosondes in Southeast Asia. New Innovation in Metallurgy and Materials, 23, 46-69. https://doi.org/10.1063/5.0002321
  2. Adam, F. (2006). Mapping social capital across Europe: Findings, trends and methodological shortcomings of cross-national surveys. Social Science Information, 47(2), 159-186. https://doi.org/10.1177%2F0539018408089077 https://doi.org/10.1177%2F0539018408089077
  3. Akcomak, I., & Weel, B. T. (2012). The impact of social capital on crime: Evidence from the Netherlands. Regional Science and Urban Economics, 42(1-2), 323-340. https://doi.org/10.1016/j.regsciurbeco.2011.09.008
  4. Alesina, A., Algan, Y., Cahuc, P. & Giuliano, P. (2015). Family values and the regulation of labor. Journal of the European Economic Association, 13(4), 599-630. https://doi.org/10.1111/jeea.12121
  5. Alesina, A., & Giuliano, P. (2011). Family ties and political participation. Journal of the European Economic Association, 9, 817-839. https://doi.org/10.1111/%28ISSN%291542-4774/issues
  6. Baker, W. E. (1990). Market networks and corporate behavior. American Journal of Sociology, 96(3), 589-625. https://www.jstor.org/stable/2781065 https://doi.org/10.1086/229573
  7. Bourdieu, P. (1986). The forms of capital. In: Richardson, J. G. (Ed.), Handbook of theory and research for the sociology of education (pp. 56-96). Connecticut: Greenwood Press, Inc.
  8. Barreto, M., & Munoz, J.A. (2003). Reexamining the "politics of in-between": Political participation among Mexican immigrants in the United States. Hispanic Journal of Behavioral Sciences, 25(4), 427-447. https://doi.org/10.1177/0739986303258599
  9. Belot, M., & Ermisch, J. (2009). Friendship ties and geographical mobility: Evidence from Great Britain. Journal of the Royal Statistical Society. Series A (Statistics in Society), 172(2), 427-442. https://www.jstor.org/stable/20622506 https://doi.org/10.1111/j.1467-985X.2008.00566.x
  10. Boix, C., & Posner, D. N. (1998). Social capital: Explaining its origins and effects on government performance. British Journal of Political Science, 18(4), 686-693 https://doi.org/10.1017/S0007123498000313
  11. Buonanno, G., Anastasi, P., Di Iorio, F., & Viola, A. (2010). Ultrafine particle apportionment and exposure assessment in respect of linear and point sources. Atmospheric Pollution Research, 1(1), 36-43. https://doi.org/10.5094/apr.2010.006
  12. Chun, J. & Sang, L. T. (2012). Research and policy dialogue on climate change, migration, and resettlement in Viet Nam. Final Report. United Nations Viet Nam, Hanoi.
  13. Cohen, S. (2004). Social relationships and health. American Psychologist, 59(8), 676-684. https://doi.org/10.1037/0003-066X.59.8.676
  14. Coleman, J. S. (1988). Social capital in the creation of human capital. American Journal of Sociology, 94, 95-120. https://www.jstor.org/stable/2780243 https://doi.org/10.1086/229033
  15. Curran, T. J., Brown, R. L., Edwards, E., Hopkins, K., Kelley, C., Mccarthy, E., & Wolf, J. (2008). Plant functional traits explain interspecific differences in immediate cyclone damage to trees of an endangered rainforest community in north Queensland. Australia Ecology, 33(4), 451-461. https://doi.org/10.1111/j.1442-9993.2008.01900.x
  16. Cheong, P. H., Edwards, R., Goulbourne, H., & Solomos, J. (2007). Immigration, social cohesion, and social capital: A critical review. Critical Social Policy, 27(1), 24-49. https://doi.org/10.1177%2F0261018307072206 https://doi.org/10.1177%2F0261018307072206
  17. David, Q., Janiak, A., & Wasmer, E. (2010). Local social capital and geographical mobility. Journal of Urban Economics, 68, 191-204. http://dx.doi.org/10.1016/j.jue.2010.04.003
  18. Deller, S., Tsung-Hsiu, T., & Marcouiller, D. W. (2001). The role of amenities and quality of life in rural economic growth. American Journal of Agricultural Economics, 83(2), 352-365. http://doi.org/10.1111/0002-9092.00161
  19. Fukuyama, F. (2002). Social capital and development: The coming agenda. SAIS Review, 22(1), 23-37. https://doi.org/10.1353/sais.2002.0009
  20. Garip, F. (2008). Social capital and migration: How do similar resources lead to divergent outcomes? Demography, 45, 591-617. https://doi.org/10.1353/dem.0.0016.
  21. Gottlieb, B. H., & Bergen, A. E. (2010). Social support concepts and measures. Journal of Psychosomatic Research, 69(5), 511-520. https://doi.org/10.1016/j.jpsychores.2009.10.001
  22. Granovetter, M. S. (1973). The strength of weak ties. American Journal of Sociology, 78(6), 1360-1380. http://www.jstor.org/stable/2776392 https://doi.org/10.1086/225469
  23. Graves, P. E., & Linneman, P. D. (1979). Household migration: Theoretical and empirical results. Journal Urban Economics, 6(3), 383-404. https://doi.org/10.1016/0094-1190(79)90038-X
  24. Glaeser, E., Laibson, D., & Sacerdote, B. (2002). An economic approach to social capital. Economic Journal, 112, F437-F458. https://scholar.harvard.edu/files/glaeser/files/economicapproachsocialcapital.pdf https://doi.org/10.1111/1468-0297.00078
  25. Guiso, L., Sapienza, P., & Zingales, L. (2002). People's opium? Religion and economic attitudes. Journal of Monetary Economics, 50(1), 225-282. http://doi.org/10.2139/ssrn.331280
  26. General Statistics Office (GSO). (2015). Statistical yearbook 2015. Hanoi: GSO.
  27. Hoang, T. N., & Truong, C. B. (2021). The relationship between social capital, knowledge sharing and enterprise performance: Evidence from Vietnam. Journal of Asian Finance, Economics, and Business, 8(11). 133-143. https://doi.org/10.13106/jafeb.2021.vol8.no11.0133
  28. Henn, M., Weinstein, M., & Forrest, S. (2005). Uninterested youth? Young people's attitudes towards party politics in Britain. Political Studies, 53(3), 556-578. https://doi.org/10.1111%2Fj.1467-9248.2005.00544.x https://doi.org/10.1111%2Fj.1467-9248.2005.00544.x
  29. Hilber, C. A. L. (2010). New housing supply and the dilution of social capital. Journal of Urban Economics, 67(3), 419-437. https://doi.org/10.1016/j.jue.2009.12.001
  30. Hotchkiss, J. L. (2018). Individual social capital and migration. Atlanta: Georgia State University. https://doi.org/10.29338/wp2018-03
  31. Hotchkiss, J. L., & Rupasingha, A. (2018). Individual social capital and migration. Urban Research eJournal, 38, 1-58. https://doi.org/10.2139/ssrn.3140804
  32. Isham, J. (2002). The effect of social capital on fertilizer adoption: Evidence from rural Tanzania. Journal of African Economies, 11(1), 39-60. https://doi.org/10.1093/jae/11.1.39
  33. Jung, M. H. (2020). The effect of social capital on personal happiness: A focus on service industry employees. Journal of Asian Finance, Economics, and Business, 7(1), 291-299. https://doi.org/10.13106/jafeb.2020.vol7.no1.291
  34. Kan, K. (2007). Residential mobility and social capital. Journal of Urban Economics, 61(3), 436-457. https://doi.org/10.1016/j.jue.2006.07.005
  35. Knack, S. (2002). Social capital and the quality of government: Evidence from the States. American Journal of Political Science, 46(4), 772-785. https://doi.org/10.2307/3088433
  36. Knack, S., & Keefer, P. (1997). Does social capital have an economic payoff? A cross-country investigation. Quarterly Journal of Economics, 112(4), 1251-1288. https://doi.org/10.1162/003355300555475
  37. Kindler, M., Ratcheva, V., & Piechowska, M. (2015). Social networks, social capital and migrant integration at the local level: a European literature review (Working Paper No. 6/2015). Birmingham, UK: Institute for Research into Superdiversity. https://www.birmingham.ac.uk/Documents/college-social-sciences/social-policy/iris/2015/working-paper-series/IRiS-WP-6-2015.pdf
  38. Lin, N. (2001). Social capital. A theory of social structure and action. Cambridge, UK: Cambridge University Press.
  39. Lindstrom, M. (2005). Ethnic differences in social participation and social capital in Malmo, Sweden: A population-based study. Social Science and Medicine, 60(7), 1527-1546. https://doi.org/10.1016/j.socscimed.2004.08.015
  40. McMillan, D. W., & Chavis, D. M. (1986). Sense of community: A definition and theory. Journal of Community Psychology, 14(1), 6-23. http://doi.org/10.1002/1520-6629(198601)14:13.0.C-O;2-I
  41. Massey, D. S., Arango, J., Hugo, G., Kouaouci, A., Pellegrino, A., & Taylor, J. E. (1994). An evaluation of international migration theory: The North American case. Population and Development Review, 20(4), 699-751. https://doi.org/10.2307/2137660
  42. Michaelides, M. (2011). The effect of local ties, wages, and housing costs on migration decisions. The Journal of Socio-Economics, 40(2), 132-140. https://doi.org/10.1016/j.socec.2011.01.010
  43. Narayan, D., & Pritchett, L. (1999). Cents and sociability: Household income and social capital in rural Tanzania. Economic Development and Cultural Change, 47(4), 871-897. https://doi.org/10.10-86/452436 https://doi.org/10.10-86/452436
  44. National Migration Report. (2015). The 2015 National Internal Migration Survey: Major findings. https://data.vietnam.opendevelopmentme-kong.net/vi/dataset/the-2015-national-internal-migration-survey-major-findings
  45. Oehmke, J. F., Tsukamoto, S., & Post, L. A. (2007). Can Health Care Services Attract Retirees and Contribute to the Economic Sustainability of Rural Places? Agricultural and Resource Economics Review, 36(1), 95-106. https://doi.org/10.1017/S1068280500009473
  46. Palmer, M. D., McNeall, D. J., & Dunstone, N. J. (2011). Importance of the deep ocean for estimating decadal changes in Earth's radiation balance. Geophysical Research Letters, 38, L13707. http://doi.org/10.1029/2011GL047835
  47. Palloni, A., Massey, D. S., Ceballos, M., Espinosa, K., & Spittel, M. (2001). Social capital and international migration: A test using the information on family networks. American Journal of Sociology, 106(5), 1262-1298. http://www.jstor.org/stable/10.1086/320817
  48. Perkins, D. D., Brown, B. B., & Taylor, R. B. (1996). The ecology of empowerment: Predicting participation in community organizations. Journal of Social Issues, 52(1), 85-110. https://doi.org/10.1111/j.1540-4560.1996.tb01363.x
  49. Perkins, D. D., Hughey, J., & Speer, P. W. (2002). Community psychology perspectives on social capital theory and community development practice. Journal of the Community Development Society, 33(1), 33-52. https://doi.org/10.1080/15575330209490141
  50. Prezza, M., Amici, M., Roberti, T., & Tedeschi, G. (2001). Sense of community referred to the whole town: Its relations with neighboring, loneliness, life satisfaction, and area of residence. Journal of Community Psychology, 29(1), 29-52. https://doi.org/10.1002/15206629(200101)-29:1<29::AID-JCOP3>3.0.CO;2-C
  51. Portes, A. (1998). Social capital: Its origins and applications in modern sociology. Annual Review of Sociology, 24, 1-24. https://doi.org/10.1146/annurev.soc.24.1.1
  52. Putnam, R. D. (1993). What makes democracy work? National Civic Review, 82, 101-107. https://doi.org/10.1002/ncr.4100820204
  53. Putnam, R. D., Leonardi, R. & Nanetti, R. Y. (1994). Making democracy work: Civic traditions in modern Italy. Princeton: Princeton University Press.
  54. Putnam, R. D. (1995). Bowling alone: America's declining social capital. Journal of Democracy, 6(1), 65-78. https://doi.org/10.1007/978-1-349-62397-6_12
  55. Putnam, R. D. (2000). Bowling alone: The collapse and revival of American community. New York: Simon and Schuster.
  56. Santosa, M. G. S., Supartha, W. G., Riana, I. G., & Surya, I. B. K. (2020). Contiguity of social capital, competence, and business performance moderating by government policy. Journal of Asian Finance, Economics, and Business, 7(9), 727-736. https://doi.org/10.13106/jafeb.20-20.vol7.no9.727
  57. Spilimbergo, A., & Ubeda, L. (2004). Family attachment and the decision to move by race. Journal of Urban Economics, 55(3), 478-497. http://dx.doi.org/10.1016/j.jue.2003.07.004
  58. Stone, W., Gray, M., & Huges, J. (2004). Social capital at work: How family, friends and civic ties relate to labor market outcomes (Working Paper No. 31). Melbourne, Australia: Australian Institute of Family Studies. https://econwpa.ub.unimuenchen.de/econ-wp/othr/papers/0408/0408005.pdf
  59. Togeby, L. (2004). How organizational participation affects political participationand social trust among second-generation immigrants in Denmark. Journal of Ethnic and Migration Studies, 30(3), 509-529. https://doi.org/10.1080/13691830410001682061
  60. Thomas, M. (2015). Social and political capital in rural Viet Nam (WIDER Working Paper, No. 2015/087). Helsinki, Finland: UNU-WIDER. https://www.wider.unu.edu/sites/default/files/wp2015-087.pdf
  61. Vietnam Access to Resources Household Survey (VARHS). (2016). Data availability report. at: https://vi.vnp.edu.vn/tailieu-tham-khao/varhs-2016/
  62. Wang, P., Chen, X., Gong, J., & Jacques-Tiura, A. J. (2014). Reliability and validity of the personal social capital scale 16 and personal social capital scale 8: Two short instruments for survey studies. Social Indicators Research, 119(2), 1133-1148. https://www.jstor.org/stable/24721474 https://doi.org/10.1007/s11205-013-0540-3
  63. Winkels, A. (2012). Migration, social networks, and risk: The case of rural to rural migration in Vietnam. Journal of Vietnamese Studies, 7(4), 92-121. https://doi.org/10.1525/vs.2012.7.4.92
  64. Yao, C., Joo, J. H., & Shin, M. M. (2016). Relationship between local SNS usage and social capital. Journal of Distribution Science, 14(8), 35-44. http://doi.org/10.15722/jds.14.8.201608.35