APPROACHES TO UNDERSTANDING MIGRATION: A MULT-COUNTRY ANALYSIS OF THE PUSH AND PULL MIGRATION TREND

Abstract

ABSTRACT. The study explores the factors that drive migration to Poland and Thailand. It investigated how economic, political, environmental, and social factors impact on workers decision to migrate in search of greener pastures. The research is hinged on the Push-Pull Migration Model. The research populations consisted of a total of 762 purposively selected respondents; 452 were selected from Bangkok and Phuket, Thailand, while 310 were selected from Warsaw in Poland. The study was quantitative research that applied SEM analysis for data interpretation. Findings indicated that 76% of the migrants to Thailand have at least a university degree compared to 24% with a high school certificate or less, while for Poland, 68% have at least a university degree compared to 32% with a high school certificate or less. SEM analysis revealed that only the economic push and pull factors were accepted in both Thailand and Poland/ The results reinforced the significant influence of unemployment, poverty, high employment, and high wages, while acknowledging the impact of political and social factors. The significance of environmental factors from the findings was underwhelming.

Headnote

ABSTRACT. The study explores the factors that drive migration to Poland and Thailand. It investigated how economic, political, environmental, and social factors impact on workers decision to migrate in search of greener pastures. The research is hinged on the Push-Pull Migration Model. The research populations consisted of a total of 762 purposively selected respondents; 452 were selected from Bangkok and Phuket, Thailand, while 310 were selected from Warsaw in Poland. The study was quantitative research that applied SEM analysis for data interpretation. Findings indicated that 76% of the migrants to Thailand have at least a university degree compared to 24% with a high school certificate or less, while for Poland, 68% have at least a university degree compared to 32% with a high school certificate or less. SEM analysis revealed that only the economic push and pull factors were accepted in both Thailand and Poland/ The results reinforced the significant influence of unemployment, poverty, high employment, and high wages, while acknowledging the impact of political and social factors. The significance of environmental factors from the findings was underwhelming.

Keywords: migration, push and pull model, Southeast Asia, Europe, Thailand, Poland

Introduction

Migration is the relocation of people from one area to another. It is generally associated with the change of residence whether temporary or permanent. Motivations for migration are inter-regional and intraregional incongruences at the macro level and essentially the absence of or limited availability of job opportunities, which normally leads to a low standard of living conditions among varying socio-economic groups at the micro level. Three components usually impact the population of any given area; they are the fertility (reproduction) rate, mortality rate and the migration trend. This study is concerned with migration trend and the social, economic, political and environmental factors that come into play under migration discourse. There are basically two types of migration; internal migration and external (international) migration. Internal migration is the relocation of people within a country, while external (international) migration is concerned with the relocation of people from one country to another. Many reasons have been proffered as the causes of migration such as better employment opportunities, better standard of living, healthcare facilities, better security etc. This study is focused on international migration that takes place in Thailand and Poland.

Studies on human migration have rapidly evolved in recent decades in the academia. Migration is a social and political activity that historically is as old as human existence on earth. Migration can be regarded as a form of repositioning or relocation that involves temporary or permanent movement from one geographical location to another. Some of the earliest reasons for migration have been in search of better opportunities; other reasons over the years have included escaping from wars, famine, drought, political, religious and ethnic persecutions, etc. in recent times, the main drivers of migration have been economic, where people from developing countries make effort both legally and illegally to move to developed societies in the west, wars and persecutions (political, ethnic and religious) have also led to migrations (Pan, 2019). The news has often reported about the plight of Africans trying to get to Europe perilously by rafts and overcrowded dingy boats (Bini, 2009; Flahaux & De Haas, 2016; Kohnert, 2007; Idemudia & Boehnke, 2020; Metcalfe-Hough, 2015). In the Southeast Asia region, Chantavanich and Vungsiriphisal (2012) reported about the historical antecedents of cross border economic migrations from neighboring countries to Thailand which has been boosted since the 1970s, the early part of Thailand's technological and economic revolution. Over the years, Thailand has become a well-known tourist destination ranked 34th in the World Economic Forum (WEF) travel and tourism competitiveness index in 2019. (WEF, 2019).

With the decline of factory workers due to Thailand's education policy where students were required to spend longer time at school, migrants became the solution to the labor shortfall and this became a pull factor that has continued to attract migrants and expatriates to the Thai labor market. Large scale migration to Thailand from the neighboring ASEAN countries increased significantly in the 1990s according to Sricharoen (2019). He adds that migration of expatriates to Thailand was boosted by the economic boom in the period, the export base, and low-cost base for multinational companies all contributed to elevate Thailand economy above its neighbors. Sricharoen (2019) enlightens that one of the outcomes of these migrations has been the ethnic mixing of Thailand's population which now includes Malay, Chinese, Shan, Karen, Khmer, Lao, Mon, Indian and others. This has led to a systematic cultural and linguistic assimilation of these diverse groups as part of Thailand's local population over time.

The narrative is also similar in Poland, as Matkowska (2013) states that foreigners are increasingly visible on the Polish labor market, and the demand for foreigners has been constantly growing. This demand has an appropriate response in form of supply of labor force of high quality, which, in turn, is caused by subjective expectation of higher quality of life (Mishchuk et al., 2019; Rauhut, 2021). This tendency is been observed not only for migration in Poland but it also typical for all countries with developed economies, especially innovatively oriented (Privara et al., 2019). Juxtaposing with the labor market of Thailand proves that employing foreigners is not only a current and dynamic trend, but a necessity in the context of maintaining the current growth pace of the economy, taking into account current demographic trends of migration (Chorągwicka - Majstrowicz, 2018). The data from Migracje (2021) shows that a migration trend in Poland has been on the increase every year; total number of foreigners requiring documentation of some form in 2019 was 381, 374 and rising to 443, 119 (14% increase) in 2021. Similarly, the numbers of those with temporary residence permits in Poland showed an increase from 215, 484 in 2019 to 312,562 (31% increase) in 2021. The United Nation (2019)'s report on Thailand migration showed an increasing number of non-Thai residents within the country, their number increased from an estimated 3.7 million in 2014 to 4.9 million in 2018. This number is made up of roughly 3.9 million migrant workers from Southeast Asia.

In many countries, the immigration phenomenon has led to conflict situations and unrest. Local people often see foreigners as a threat to the labour market. Foreigners who have not found a job may also require financial support, which locals complain diverts funding for other programs that may benefit citizens (Cancryn, 2021; Chaiyasoonthorn, Khalid, & Chaveesuk, 2019; Diamond, 2018; Guzi, Kahanec & Ulceluse, 2021; Schilling et al., 2017; Verza, 2020). Cases also arise from tourists who turn short visits into longer and permanent stays (Kaosa-ard, 1994; Phiromyoo, 2011). It also happens that illegal employment of foreigners leads to large financial losses in the economy. The growing conflicts between foreign cultures are also a negative phenomenon. Immigration also has positive aspects, such as profitability in employing foreigners by companies, as well as increasing competitiveness on the labour market, which makes employees more efficient and entrepreneurial. Mixed teams also lead to the exchange of experiences and cultures between employees, with many of the foreign expatriates assimilating quite fast in new conditions. A positive phenomenon of immigration is also the fact that it significantly affects economic growth, which is a key factor increasing the level of wealth in a country (Boswell & Straubhaar, 2004; Edwards & Ortega, 2016; Muangmee et al., 2021).

Immigrants can be divided into two main groups; people with higher education, who may affect the growth in the number of highly skilled workers, e.g. engineers and physicians (Bilan et al., 2020; Klimek, 2015; Wróblewski & Dacko-Pikiewicz, 2018), and those with lower education such as warehousemen, construction workers, barmen etc. (Peri, 2016; Szczepańska-Woszczyna, 2014). Educated expatriates are an extremely valuable human capital; they lead to an increase in the number of qualified people in a given labour market. This is related to the difference in the quality of education obtained in another country, the level of knowledge and the speed of acquiring foreign languages, which may affect the integration process and employment of expatriates in a given country (Bilan et al., 2019; Sharaf, 2013). The reasons for such economic migration may be for better working conditions and better social benefits (Krutova, 2019; Haque & Oino, 2019; Meekaewkunchorn et al., 2021). The fact that immigrants are diverse in terms of education and skills on the labour market means that they can be delegated to various tasks. However, the earnings of expatriates may be lower than those of native citizens and the achievement of a satisfactory income for immigrants may extend significantly over time (Aringa, Lucifora, & Pagani, 2015).

The reason for the difference in earnings is the occurrence of occupational mobility phenomenon and its consequences, because many immigrants often experience negative changes in their career status when looking for new jobs and rotation between companies during their stay in another country (Javdani & McGee, 2018). For many groups of expatriates, the difference in remuneration is significant and the reasons may be their skills, origin and language level (Myślicki, 2016; Wróblewski, 2017). It is therefore necessary to support countries and political changes which will facilitate the adaptation of immigrants, may reduce entry barriers and facilitate the process of cultural assimilation (Anderson & Huang, 2019), which may result in attracting foreigners. Different countries have numerous programmes to support immigrants in their mobilisation due to their unfavourable situation on the labour market. It is often the case when immigrants have less chance of being employed than native citizens and are often listed as unemployed. To facilitate the situation of immigrants on the labour market, European governments use Active Labour Market Programmes, which can include language courses, job search assistance and numerous training programmes, which are effective tools to support both working as well as job-seeking immigrants, effectively reducing the number of unemployed immigrants (Butschek & Walter, 2014). Such support programmes can also contribute to improving cultural assimilation increasing their overall level of satisfaction and sense of belonging to a country (Chaveesuk, Khalid, & Chaiyasoonthorn, 2020; Kóczán 2016; Dacko-Pikiewicz & Wróblewski, 2017; Martin & Zurcher, 2008).

This study aims to analyze the expatriate migrant data in Thailand and Poland with a view to understand the dynamics in both countries by conducting a cross-country analysis that compares the results of the two countries. The motivation for comparing Thailand and Poland is based mainly on the facts that both are emergent nations and not considered the traditional power hubs in their regions and share the characteristic of similar development trend that is focused on an efficiency-driven economy as stated by Tripopsakul (2018). Migration is an important issue in both countries with global perspective and has implications that spread across their international boundaries. With this in mind, this study tried to understand the rationale and drivers of migration to the two countries. The objectives of the study include;

- To ascertain the role of economic motivation in migrations to Thailand and Poland.

- To find out the political motivation of migrations to Thailand and Poland.

- To find out the impact of environmental factors in migration decisions by expatriates to Thailand and Poland.

- To ascertain the social factors that drive migrations to Thailand and Poland.

1.1.Migration pattern in Thailand and Poland

Expatriate migration in Thailand is driven primarily by geographical considerations, with most trans-border movements' occurring between neighboring ASEAN countries. These movements are greatly influenced by economic and labor market inequalities, which cause expatriates to migrate from lower-income nations to higher-income nations (Sricharoen, 2019). The benefits of expatriates to the local economy are to help drive the country's export-oriented economy and make contributions to the high GDP growth. In countries of origin, migration has an even larger impact. Ladek (2018) posits that there exists a strong relationship between migration and poverty reduction especially within the nations of Southeast Asia. Migrants in Thailand Poland frequently make remit a considerable portion of their wages and income as savings back to their family and friends in their home countries. These earnings repatriated back home help to improve the life and welfare of their family and friends, contributing to their education, healthcare and general improvements.

Chintayananda, Risser & Chantavanich (1997) trace the origins of the first official permission to allow unskilled migration from Myanmar to work in Thailand was announced in 1992. It started with permission to four border provinces and was later increased to nine provinces. In 1996, The Thai government issued a resolution allowing for migration from Cambodia and Laos. Most of these migrants were allowed to do labour intensive manual jobs in Thailand without formal documentation with the idea being for them to be temporary migrants. The economic crises that hit Thailand in 1997 led to unemployment in Thailand and led to the deportation of about 300,000 migrant workers to allow more local workers get employed. In 2001, the Thai government granted amnesty to unregistered migrants in the country, this was revised in 2003 to legalize irregular unskilled migrant workers. The formal registration took place in 2004 and revealed a total of 1,284,920 unskilled migrants with 93,083 children aged 0-15. Subsequent re-registration in 2005 revealed a reduced number (343,777) of registered migrant workers.

Poland released a list of professions that would be eligible to obtain work permits from July 1, 2018, onward. The list contains professions for which migrants can apply for a work permit without conducting a test of the labour market, but it is still required that the applicant demonstrate possession of the requisite skills and qualifications for the job for which a work permit is being sought. This policy was implemented by the regulation from June 28, 2018, amending regulation of the Ministry of Family, Labour and Social Policy (Official Codification Journal of Laws 2015, Item 97 as amended). The purpose of this amendment was to aid expatriates to have access to the labour market especially their actual professions. It also increases the collection of cases, where the province governor can issue a work permit without conducting a test of the labour market (Grykowska, 2018; Vveinhardt & Kuklytė, 2016). Typical professions eligible for work permits are in industrial and production engineering, electrical engineering, professions associated with the laboratory analysis of computer systems and IT industry as development of computer systems, programming, creating apps, designing operations and database management. Professions with a university degree title of technician such as electrical technician and related professions were also included. Other such as well as lorry drivers, crane specialist and operators of other earth moving equipment etc. are exempt. To sum up problems created by convoluted processes and long waiting times required for resolving work permit related issues as it was becoming a barrier in particular for employees and employers. The main problem faced in the management of immigration details are long queues at offices and administrative procedures that are repeated severally causing delays.

2.Literature review

The influence of migrants on the economy and the labour market operations have been discussed to some extent (Chreim et al. 2018; Cristea & Grabara, 2019; Rausser et al., 2018; Oláh et al., 2017; Cseh Papp, Bilan & Dajnoki, 2018; Bite, Konczos-Szombathelyi & Vasa, 2020; Oliinyk et al., 2021; Simionescu, Bilan & Mentel, 2017), as well as the problems migrants may face in their search for jobs (Jędrzejowska-Schiffauer & Schiffauer, 2017; Piekutowska & Fiedorczuk, 2018; Szczepańska-Woszczyna & Kurowska-Pysz, 2016). The enormous expansion of low-paying, unskilled, contracted expatriates' mostly single men on fixed contracts and professionals who are offered competitive remuneration packages that includes long-term engagements has been analyzed by Tahir and Egleston (2019). Thus, an economy becoming alluring to highly skilled labour from abroad is very central in manpower planning at the nation-state level (Findlay, 2006; Mercer Consulting, 2012), where the labour force mobility functions as a facilitator to fill skilled labour openings and deal with the consequences of skilled labour shortages at the same time improving the employability and engagement of the expatriates involved (McNulty & Inkson, 2013; Miłaszewicz et al., 2015; Vaiman & Collings, 2013). Many countries have lowered immigration barriers in order to attract highly skilled temporary and permanent employees with other incentives added by some countries to induce expatriates into committing to long-term contracts and dissuade them from moving to other countries (Bashin & Cheng, 2002; de Haas, 2021; Legget, 2013). Lavenex (2006) notes that the flexibility of highly skilled workers towards relocation to better contract terms in other countries is a concern and is part of "the market-led, multilateral framework of international trade and competition not just between companies, but also between nations" (p. 52).

In trying to understand the motivations that make skilled and unskilled professionals migrate from their country of origin or a secondary migration process where expatriates switch from a country they migrated to for another in search of better remunerations/working conditions, the study adopts the Push and Pull Theory of Migration framework of Lee (1966) to deconstruct the attraction of migrants to Thailand and Poland. The theory's main postulation is that migration is determined by push and pull factors; these are the forces that induce people towards moving to a new geographical location, these factors could be economic, social, political or environmental. Push factors are conditions that can force people to leave their homes and are related to the country from which a person migrates. They include non-availability of opportunities, poverty, insecurity, over-population, poor living conditions, desertification, famines/droughts, fear of persecution (political, religious, ethnic, gender, sexual orientation) poor healthcare, loss of wealth, and natural disasters. Pull factors are the reverse of push factors; they draw people towards certain locations because of the benefits on offer. Pull factors include better job opportunities and working conditions, better living conditions, effortless availability of land for settling and agriculture, political/religious/ethnic/gender/sexual orientation freedom, better education facilities and assisted welfare systems, better commuting network and communication facilities, better healthcare system and stress-free serene and attractive environment and systems in place to tackle natural hazards, better security and equality before the justice system (Chatterjee & Mishra, 2018). Table 1 summarizes Push and Pull factors.

The Push and Pull theory has been analyzed from a number of perspectives, Dorigo and Tobler (1983) developed it into a mathematical form in their quintessential study, other empirical researchers have identified several factors that have affected migration decisions by expatriates, it has been explored from the position of income inequalities (Banerjee, 1991; Borjas et al., 1992; Roback, 1988, 1982), basic amenities (Roback, 1988), social adjustment policy (Al-Srehan, 2020), migrants nets development (Andersson, 2019; Mohamed-Salem, 2020), work satisfaction and opportunities (Banerjee, 1991), better education facilities (Borjas et al., 1992; van Ham, 2001), entrepreneurial intentions of young graduates (Ojiaku, Nkamnebe & Nwaizugbe, 2018), environment and climate (Roback 1982). Lee's (1966) Push-Pull theory was inspired from Ravenstein's (1885, 1889) 'Law of Migration'. Ravenstein's study was based on the British Census of 1881. Samers (2010) informs that Ravenstein's laws are empirical generalizations founded on his estimates from the British and other censuses of the era. They were more concerned about internal migration than cross-country. The laws are summarized underneath.

- Migrants tend to move mainly over short distances; the destination of those who travel longer distances is usually great centres of commerce and industry

- Migration is usually from agrarian rural areas to industrial hubs.

- Population of large towns tend to grow more by migration than birth rate.

- The development of industry, commerce, and transport encourages migration.

- Each stream of migration produces a counter-stream.

- Over short distances, females migrate more than men, while over international distances, the men seem to be dominant.

- Economic reason is the major migration driver.

Lee (1966) modified Ravenstein's (1885) 'Law of Migration' with the publication of his paper 'A Theory of Migration.' The theory is hinged on the principles of sociology and attempts to explain the volume of migration between origin and destination. Lee's theory is important because it is easy to comprehend and has been tested and proven over the years. Lee conceptualized the factors linked with the decision to migrate and the migration process four groups:

- Factors associated with the area of origin;

- Factors associated with the area of destination;

- Intervening obstacles; and

- Personal factors.

Lee expounds that for the four groups, there are many factors which act to encourage people to move away from an area, or to encourage people to remain in an area or to attract people to an area. In this regard, there are considerable dissimilarities between the factors linked with the area of origin and those linked with the area of destination. People make the decision to migrate after taking these factors into cognizance. It is important to note that migrants usually have a better and profound understanding of the environment where they are migrating from while information about the destination may be hazy or from non-direct sources, if the sources of knowledge are direct, it is mostly limited and superficial. Technological advancements have minimized the limitations of distance and transportation.

Push factors are present in the home country where the expatriate intends to migrate from; they are the motivations that push the expatriate into migrating to the destination area. Some of them are presented in Table 1. Pull factors exist at the destination area, they are the attractive factors which the expatriates are drawn to such as readily available jobs, better healthcare. Push and pull factors work in harmony, and mostly do not co-occur, rather, the pull factors serve as the model that draws the expatriate away from the push factors which are regarded as a hindrance towards the personal and professional development of the expatriate. Therefore, if there is a lack of viable jobs or opportunities of growth within the industry, the destination country has a remedy to this in the form of readily available jobs and opportunities of growth and personal development on the job. From the analysis, we can deduce that the negative factors in expatriate home country encourage residents to move out and positive factors in the destination country attract people to move there. Fouberg et al. (2009) identifies push-pull factors to include economic conditions, political circumstances, environmental conditions, culture and traditions and technology advances. This study attempts to validate these factors to explore how they affect the decision of migrants to leave one country for another.

Various studies have explored the push and pull theory; Mazzarol and Soutar (2002) investigated the factors that motivated international students choice of foreign country to study using the push and pull theory. They examined the impetus behind the students' decision making from choice of foreign universities to final destination. The results revealed that economic and social factors were the predominant push factors that influenced students' final decisions on choice of destination country. Nevertheless, the pull factors consisted of variety of issues from economic, social, quality of education, political and environmental. In a study of the internal people relocations in the counties of Shandong Province in China between 2000 and 2018, Wang et al. (2021) analyzed the factors that influenced country level city shrinkage using the push-pull theory. They analyzed the push-pull mechanism using a dynamic correlation testing and the granger causality test. Their findings showed that the country-level shrinkage was impacted by lack of resources, slow economic growth rate, declining quality of life in the cities as push factors on the declining population. The pull factors attracting them to other Chinese cities were equality in public service placements, healthy living environments, and a slowing down of relative deprivation. We can see some similarities in push-pull factors influencing both internal and international migration tendencies (Parkins, 2010; van Hear, Bakewell & Long, 2017; Zhang, Zhang & Zhang, 1997)

Political instability and government repression as push factors have created a migration problem globally. More recently seen in uprisings in the Middle East where the ouster leaders in Libya and civil strife in Syria and the US-led war in Afghanistan, while conflicts in Eritrea, Somalia, Mali, Cameroun and Nigeria's Boko Haram terrorists have created thousands of migrants, with most trying to escape the violence to countries that are politically stable and free of government repression. The fear fueling migration is when people feel they are deprived of basic human rights, education and the right to a dignified life as seen in the ideologies of Taliban in Afghanistan and Boko Haram in Nigeria. The latter has been estimated to cause the internal displacement of over 2 million internally and externally in Nigeria (Castelli, 2018; Internal Displacement Monitoring Centre, 2017; International Organization for Migration, 2018). Historically, Thailand has been a safe haven for many running away from political violence and government repression especially in neighboring Southeast Asian countries. The coming to power of the People's Republic of China in 1949 led to the migration of thousands to Taiwan and many others to northern Thailand where they reside to this day (Robinson, 1996).

Thailand again received thousands of migrants from Vietnam when war broke out between France and the Viet Minh resistance group after WWII, and again after the establishment of Vietnam. Many returned after the violence but about 36, 000 stayed back in eastern Thailand, and more than half of them were born there (Robinson, 1996; Amarapibal, Beesey & Germershausen, 2003). Thailand also served as sanctuary to hundreds of thousands of Cambodians during different periods; first from those fleeing the dictatorial and brutal Khmer Rouge regime, and then again, after the regime was ousted leading to a civil war, and the violence that followed which continued from 1975 and ended in 1992 (Huguet & Punpuing, 2005). Many citizens of Myanmar have been resident in Thailand to escape repressive regimes. Chantavanich & Vungsiriphisal (2012) inform that many Myanmar migrants contribute millions of Baht in remittances to Myanmar annually to support relatives back home. A survey of Myanmar migrants in Thailand these migrants contribute millions of baht in remittances back to Myanmar annually to support their families back home. The migrants plan to return home under improved conditions in the future when they have saved enough to start life back home, with more job opportunities available that offer wages high enough to support a decent lifestyle, under a stable political government and sufficient infrastructure.

Shrestha (2017) tested the push and pull theory on the migration patterns from Nepal using 452 rural villages over three periods in the 2000s. The study utilizes rainfall shocks and deaths arising from conflict as push factors and growth in the manufacturing and construction sectors in destination countries as pull factors. Analysis showed that when household income increases by US$100 due to rainfall shock, migration to India increases by 54%, however, there is no effect on migration anywhere else. Also, an increase in conflict reduces the consumption and availability of basic amenity among the wealthier population, higher rates of migration especially from the urban areas in Nepal. An increase in demand from the destination countries, especially Malaysia and the Gulf countries significantly affects migration to those destinations. The results were consistent with the postulates of Lee (1966) push and pull model. Thus, an increase in income for Nepalese residents' increases migration rate to India, while a reduction in the cost of migration may increase profitable migration in other places, and expatriates with migration mindset will be willing to hedge on the advantages that these opportunities provide.

Zanabazar, Kho and Jigjiddorj (2021) studied how push and pull factors affected the migration pattern of Mongolians to the Republic of South Korea. The survey was conducted among Mongolian expatriates residing and working in the urban cities of Incheon, Ulsan, and Seoul (the capital city). Several statistical techniques were employed in testing the validity and reliability of the study data, including factor analysis to confirm that each variable applied was correctly measured, correlation analysis to evaluate the strength of the correlation between the independent and dependent variables, and multiple regression analysis to predict the value of variables employed in the research. Findings revealed that the economic push factor was the dominant factor arising from low and unstable income, poverty, and economic upheavals as motivations that led to their migration. Similarly, economic pull factors were also the main incentive for migration to South Korea, with significantly higher wages, health and wellbeing, the opportunity to save and social factors, such as access to quality education, the cultural experience and adventure, and reuniting with relatives and family members already settled in South Korea. The major difference between this study and the literature reviewed is that this study will use a cross-country multigroup analysis compared to the others that applied single country and in-country analysis.

The conceptual framework was developed from a comprehensive and critical review of the literature as illustrated in Figure 1. The conceptual framework comprises of four variables,

The following hypotheses were formulated from the framework of the study, they include;

H1: Economic factors such as unemployment and poverty are push factors for migration from home country.

H2: Political instability and government suppression serve as push factors for migration from home country.

H3: Environmental factors like natural disasters and drought are push factors for migration from home country.

H4: Social factors like social inequality and poor medical facilities serve as push factors for migration from home country.

H5: Economic factors like high employment opportunities and high wages serve as pull factors for migration to Thailand/Poland.

H6: Political factors such as political stability and good security serve as pull factors for migration to Thailand/Poland.

H7: Environmental factors like land fertility and good atmosphere serve as pull factors for migration to Thailand/Poland.

H8: Social factors such as social satisfaction and social status serve as pull factors for migration to Thailand/Poland.

3.Methodology

The research was an empirical investigation of the factors that influenced migration to Thailand and Poland. The study was underpinned by the Push and Pull Theory of Lee (1966) on the push factors that encourage migrants to leave one country and the pull factors that attract migrants to another, in this case Thailand and Poland. A quantitative research design was employed to carry out the research. Primary data was collected using a questionnaire from the sample population made up of migrants in Bangkok and Phuket in Thailand, and Warsaw in Poland. The cities were selected because data on migrants to both countries showed that most migrants settled in those cities more than any other in the country (Chorągwicka - Majstrowicz, 2018; Sricharoen, 2019), and so, will have adequate respondents serve as sources of quality data. A total of 762 respondents were sampled for the study, 452 respondents were selected in Thailand while 310 were selected in Poland based on the migration trends identified (Chorągwicka - Majstrowicz, 2018; Sricharoen, 2019). Migrant workers were identified at different locations in Bangkok and Phuket, Thailand. Both areas are known for their migrant populations in Thailand (Chantavanich & Vungsiriphisal, 2012; ReliefWeb, 2019). Data for Poland were collected mainly from migrants based in Warsaw, Poland. Purposive sampling technique was used as sampling method. Hejase and Hejase (2013) state that for large study population with gender distribution equally at 50%, e=5% (maximum tolerance away from the mean) and 95% statistical significance (Z=1.96), then the minimum sample size needed is 384. The study sample exceeds this threshold and is thus valid.

The questionnaire was made of two sections; the first section was used to collect data on the demographics of the respondents such as gender, education, marital status, employment status, income before migration, age, family size, number of children, knowledge and attitude about destination country, financial status in Thailand/Poland, among other demographic information. The second part of the questionnaire contained data on the push and pull factors that influence migration, such as the economic, social, political and environmental factors, which were developed from the literature review and presented graphically in the conceptual framework. A 5-point Likert scale was used to collect data, the measurement ranged from 1 - strongly disagree to 5 - strongly agree. The questionnaire was developed into "Thai and Polish languages" to ensure there were no difficulties in understanding the text of the questionnaire and to guarantee the quality of data. Structural Equation Modeling was applied to analyze the data. The data collected from the respondents were filtered, and tested for reliability and validity, and an analysis was conducted. The SEM analysis was used via AMOS version 26.

3.1.Reliability and validity

The study conducted an evaluation of the model through a reliability and validity analysis to evaluate the hypotheses. The validity analysis was conducted using Average Variance Extracted (AVE) while the Reliability Analysis was conducted through the Construct Reliability (CR). Amos v26 was used to conduct the reliability and validity analysis. The CR and AVE formulas applied are presented below.

Tables 2 and 3 below show the variables used for the study, their factor loadings, the estimates indicators, the construct reliability (CR) and the average variance extracted (AVE). The threshold used for the analysis was that the AVE should be greater than 0.5 (Fornell & Larcker, 1981), factor loadings should be greater than 0.5, while the CR should be greater than 0.6 (Hair et al., 2006). The obtained results for Thailand and Poland immigrants revealed that all the three thresholds were achieved. A breakdown is presented blow.

From Table 2, Cronbach's Alpha ranged between 0.602 and 0.909, while the AVE ranged between 0.501 and 0.816. From the results, all factor loadings, Cronbach's Alpha and AVE values meet the recommended standard.

Table 3 shows that the Cronbach's Alpha ranges between 0.610 and 0.875, while the AVE ranged between 0.509 and 0.878. The result indicates that all factor loadings, Cronbach's Alpha and AVE values are within the recommended standard.

4.Empirical results and discussions

The demographic characteristics of the respondents in Thailand and Poland are presented in Table 4. It shows that the age groups with highest representations in the sample were those aged 21-30 and 31-40 with 37% and 33% respectively, while the age group least represented were those above 51 with 5% of the total migrant populations in both countries. Gender information of the immigrants reveals that male dominated the female with 54% of the total respondents. However, when looking at the migrant data for each country, females were dominant in Thailand (53%) while males were dominant in Poland (64%). In terms of the marital status, there were more singles (47%) compared to married people (37%) as migrants in both Thailand and Poland. The demographic data also showed that 77% were currently employed while 23% are unemployed. Those with university/college education were dominant with 47% followed by those with high school education or less with 27% and lastly those with postgraduate degrees make up 24%. The findings also revealed that most of the migrants were knowledgeable about the country of migration 87% compared to those with little or no idea (13%) about the country of migration. The dominant occupation sector of the migrants was in construction (24%) followed by services (21%) while the occupations with the least representation were fisheries (1%), others (2%), and transport (3%). Most of the respondents funded their migration through personal savings (46%), those who were supported by family and friends made up 26%. Loans were the least source of funds for migration by the respondents (13%).

The education demographic of the respondents reveals that 73% of the migrants have at least a university degree indicating a very educated and mostly skilled workforce. The effect of such a workforce on the economy significant, that authors (Klimek, 2015; Wróblewski & Dacko-Pikiewicz, 2018) have recognized their contributions to the economy as professionals. Some have been recognized as doctors, engineers, nurses, start-up founders etc. Sharaf (2013) also discussed the importance educated expatriates as valuable human capital and their availability in the labour market increases the number of qualified people accessible to employers of labour. The finding does indicate that Thailand has more expatriates with at least a university degree (76%) of the respondents compared to Poland (68%). This finding may be affected by the fact that Thailand has nearly twice the population of Poland and the ranking of Thailand as one of the top destinations for travellers (World Economic Forum, 2019).

Literature already revealed how Poland gives priority to certain professions with higher educational qualifications, and such professions would be eligible to obtain work permits from July 1, 2018, onward. The list contains professions for which migrants can apply for a work permit without going through labour market tests, although applicants need to demonstrate their competence and qualifications in being able to perform the jobs for which work permit is being applied for. This policy was implemented by the regulation from June 28, 2018, amending regulation of the Ministry of Family, Labour and Social Policy (Official Codification Journal of Laws 2015, Item 97 as amended). Scholars (Grykowska, 2018; Vveinhardt & Kuklytė, 2016) opined those professions eligible include industrial and production engineering, electrical engineering, professions associated with the laboratory analysis of computer systems and IT industry as development of computer systems, programming, creating apps, designing operations, database management and professions that have a university degree title of technician such as electrical technician and related professions. Table 4 showed that occupations where such professions are found such as construction (24%), services (21%), production (12%), health (11%) had higher number of migrants compared to occupations that require little to no formal education such as housework (8%) and transport (3%). It shows the emphasis placed on education by immigrants.

The CFA results for Thailand indicated that the chi-square statistic for the model was significant (x2 [115] = 354.725, p < 0.05) and x2/df ratio = 3.125. This is considered acceptable as it is below the threshed of 5 and was being influenced by sample size (Schumacker & Lomax, 2004). However, the p-value was less than 0.05 (below the recommended threshold of 0.05). However, this research relied on the argument that x2 statistic and its associated p-value is very sensitive to sample size and is no longer mainly relied upon as a basis for acceptance or rejection (Schlermelleh-Engel et al. 2003; Vandenberg 2006). Therefore p-value was ignored and additional fit indices (CFI, TLI, NFI, and RMSEA) were adopted to test the fitness of the model. The CFI is 0.915; TLI is 0.901; NFI is 0.929, and they have provided an excellent fit since the values are more significant than 0.9 or close to 1.0. Additionally, the RMSEA is 0.061 (below the threshold of 0.80 as indicated in Schumacker and Lomax (2010). Since all the other model fitness tests were satisfactory, the unsatisfactory p-value was ignored. The bases of this were that Chi Square is a non-parametric statistic, and it is very sensitive to sample size. Since sample size is large - normally more than 200 is already considered large - its p-value will tend to be very small and deem to be significant and reject the status quo of the test (null hypothesis) that the sample follows normal distribution; therefore, the overall results of the CFA for Thailand indicated that it is feasible to move on and conduct the Structural Equation Modeling (SEM). A summary of the model fit for Thailand results is presented in Table 5. The path model of the analysis is also presented in Figure 2.

4.1.Structural equation modeling for Thailand

The structural equation modeling was calculated to evaluate the eight hypotheses that covered the push and pull factors of the study, they represented the relationship between the study variables. The output of the SEM model is presented in Table 6 and Figure 3.

From the results for Thailand, it was discerned that hypotheses 1, 2, 4, 6, and 8 were partially accepted as only one of the observant variables was significant. Hypotheses 3 and 7 were rejected by the results while hypothesis 5 was accepted. Figure 3 highlights the standardized estimates of the loadings and the r-squared values of the indicator variables. The CFA model fitness criteria as indicated on Table 5 show that the initial model fits well with the study data.

The CFA results for Poland show that the chi-square statistic for the model was significant (x2 [113] = 361.473, p < 0.01) and %2/df ratio = 3.242. This indicator is acceptable as it is below the threshed of 5 which Schumacker and Lomax (2004) consider as acceptable. However, the p-value was less than 0.05 (below the recommended threshold of 0.05). However, this research relied on the argument that x2 statistic and its associated p-vale is very sensitive to sample size and is no longer mainly relied upon as a basis for acceptance or rejection (Schlermelleh-Engel et al. 2003; Vandenberg 2006). Therefore p-value was ignored and additional fit indices (CFI, TLI, NFI, and RMSEA) were adopted to test the fitness of the model. The CFI is 0.935; TLI is 0.953; NFI is 0.923, and they are all considered excellent fits since their values are more significant than 0.9 or close to 1.0. Also, the RMSEA is 0.067 was also acceptable because it is below the threshold of 0.80 as suggested by Schumacker and Lomax (2010). The results of the CFA for Poland show that it is feasible to conduct the Structural Equation Modeling (SEM) analysis. A summary of the model fit for Poland result is presented in Table 7. The path model of the analysis is also presented in Figure 4.

4.2.Structural equation modeling for Poland

The structural equation modeling for Poland was calculated to evaluate the eight hypotheses that covered the push and pull factors of the study, they represented the relationship between the study variables. The output of the SEM model for Poland is presented in the Table 8 and Figure 5.

The results for Poland showed that hypotheses 1, 2, 5 and 8 were considered significant and accepted; hypotheses 6 and 7 were partially accepted while hypotheses 3 and 4 were rejected based on the respondents' answers to the questions posed to the respondents.

Economics & Sociology, Vol. 14, No. 4, 2021

Figure 5 shows the standardized estimates of the loadings and the r-squared values of the indicator variables. The CFA model fitness criteria indicate that the initial model fits well with the data. The purpose of this model was to evaluate factors that influence migration to Thailand and Poland, by applying the Push and Pull model. From the results, the economic factors analyzed for the study (hypotheses 1 and 5) - push factors of unemployment and pull factors of high employment opportunities and high wages were the most significant influences that made expatriates leave their countries for Thailand and Poland. In fact, H5 is the only hypothesis accepted in both countries from the study. This indicates the high value placed on economic factors as the main driver of migration. This has been captured by a number of studies such as Banerjee (1991), Krutova (2019), Haque and Oino (2019), and Pan (2019) who informed that immigrants attribute economic reasons such as better job opportunities and higher pay as motivations for seeking opportunities in abroad. (Sricharoen, 2019) added that these relocations are fuelled by economic and labor market inequalities, which cause expatriates to migrate from lower-income nations to nations with higher wages. Wang et al. (2021) adds that push factors such as dearth of resources, slow economic growth rate as push factors that encourage migration of expatriates, and the results agree with those expressed by the respondents in Thailand and Poland.

Similarly, the study findings revealed the significant role of unemployment as a major factor that make expatriates leave one country for another in search of better job opportunities for migrants in both Thailand and Poland. Respondents in Poland accept the significance of poverty in their decision to migrate but those in Thailand rejected the notion that poverty concerns was a significant factor in their decision to migrate. Ladek (2018) highlighted the existence of a strong link between migration and poverty reduction especially within the nations of Southeast Asia. The study findings agree with the views of Ladek when applied to Poland, but disagrees with it especially as it pertains to the influence of poverty in decisions to migrate to Thailand, considered one of the agricultural and industrial hubs of Southeast Asia. Generally, expatriates are known to make considerable financial remittances back to their countries of origin. It was thus, fascinating that migrants in Thailand do not consider poverty as a significant reason for migrating to Thailand, although they agree that opportunities exist for better paying jobs compared to their home countries. The findings also agree with those by Zanabazar et al. (2021) that economic push factor was the dominant factor arising from low and unstable income, poverty, and economic upheavals as motivations that led to their migration.

The influences of political factors were addressed in hypotheses 2 and 6. The former dealt with the push factors while the latter was concerned with the pull factors of migration. H2 was accepted by the results from Poland, while the other hypotheses for both Poland and Thailand were partially accepted with varying results. The results for Thailand were unpredicted because political instability and government suppression are mostly identified together. It was thus unexpected for migrants in Thailand to consider political instability as a push factor that influences migration while government suppression was not a significant factor unlike migrants in Poland who considered both as significant factors in their decisions to migrate, this is supported by a number of scholars (Castelli, 2018; Fouberg et al., 2009; Pan, 2019; Robinson, 1996) who view political instability and government suppression leading to civil strife and wars as push factors that encourage migration. They Castelli (2018), Huguet and Punpuing (2005), and Chantavanich and Vungsiriphisal (2012) were able to document the contributions of Thailand as a protective refuge for people especially in neighbouring countries in Southeast Asia. The findings indicate that although migrants in Thailand and Poland reject the statement that moving to Thailand and Poland was motivated the need for political stability, good security was however, accepted as a factor that influenced their migration decision as indicated by Castelli (2018), and Pan (2019).

Hypothesis 3 and 7 were rejected by both expatriates in Thailand and Poland. It means immigrants do not consider environmental considerations when making decision to move to either country. The findings do not agree with the position expressed in Pan (2019) that one of the reasons for migration is to escape drought, nor with the views of Wang et al. (2021), that healthy living was one of the lures of migrating abroad. The findings that land fertility and good atmosphere were part of the attractions were rejected by the findings by respondents in Thailand and Poland. It beckons that, although studies such as Fouberg et al. (2009) identified environmental conditions as push factors that influence decisions to migrate to other countries, Roback (1982) and Shrestha (2017) similarly discussed the impact of climatic and environmental factors as influences of migration, this study finding, however, disagree with their assertions. This is quite noteworthy as probably, future studies may seek to study environment factors as push and pull influences of migration to ascertain if there are variables that were not explored by this study such as climate change, rainfall, weather, typhoon, landslide, snow, avalanche, earthquakes, and volcanic eruptions etc.

The results for hypotheses 4 and 8 indicate partial acceptance of the results except the push factors of hypothesis 4 for Poland which the study results rejected. Whilst respondents in Thailand accepted the push factors of social inequality, they rejected the notion that poor medical facilities accelerate decision to migrate. In contrast to the findings by Poland respondents that rejected both outcomes. Again, Thailand respondents rejected the impact of social satisfaction as an enabler of migration but accepted that social status played a significant role in the decision to migrate. Poland respondents on the other hand accepted hypotheses 8 and agreed that social satisfaction and social status play a significant role in the choice of Thailand and Poland as places to migrate to. Mazzarol and Soutar (2002) have shown us in the literature how such factors were prevalent considerations in the choice of destination countries. Their views were supported by the findings in Zanabazar et al. (2021). Roback (1988) earlier discussed the influence basic amenities in decisions to migrate, the study findings, however, negate the significance of medical facilities as being part of influences to migrate. The reasons may be that most of the immigrants may be from European and Asian countries that may have medical facilities similar to what is available in Thailand and Poland, hence medical facilities.

5.Conclusions

In conclusion, this study has been able to reinforce the significance of economic pull factors such as availability of jobs and high wages as the main drivers of migration and is applicable for migrants to Thailand and Poland. Push factors also contributed in different ways to strengthen the resolve of migrants to leave their countries in search of better opportunities, some of these include; unemployment, low paying jobs that put workers in poverty, wars, conflicts, political instability, repressive dictatorships regimes, and social factors. For most of the migrants, environmental factors are not major contributors to decision to migrate. The study also highlighted the role of education in decisions to migrate as more educated people are increasingly mobile and consider traveling to other countries that offer relatively higher pay packages compared to what is available in their home countries. The analysis of literature has also revealed that migration is a continuous cycle and people will always find a reason to migrate, governments can ease the migration process by putting in place policies and regulations that engender assimilation for expatriates and migrants in new countries.

Sidebar

Khalid, B., & Urbański, M. (2021). Approaches to understanding migration: A multi-country analysis of the push and pull migration trend. Economics and Sociology, 14(4), 242-267. doi:10.14254/2071-789X.2021/14-4/14

Received: April, 2021

1st Revision: November, 2021

Accepted: December, 2021

JEL Classification: F22, F24, J61

References

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