Factors Affecting Employment Decisions in Tourism Sectors: A Case Study of the Southern Red River Sub-Region, Vietnam

Abstract

Tourism has always played an important role in socio-economic development in Vietnam and in many countries around the world. Tourism is also an industry that has attracted a large number of workers in the past two decades in Vietnam in general and territories in particular. Over the past two decades, tourism in the southern Red River sub-region has created thousands of jobs for local workers and neighboring provinces. The study aims to examine the factors affecting the employment decision of workers in the tourism industry in the South Red River sub-region. Using a pilot study surveying 10 workers in three provinces to adjust the questionnaire and a sample data of 193 observations were performed. The experimental results prove that the independent variables explain 64% of the variation of the dependent variable, and other reasons can explain the rest (36%). Research results show that four factors, namely, welfare (WE), working conditions (IN), the potential for tourism development (POT), and development policy (POL) have a positive impact on the employment decision of workers. Meanwhile, the two factors that are tourism cooperation (CO)and Education (EDU), have an insignificant impact on the employment decision of workers in the southern Red River sub-region.

1. Introduction

Tourism contributes greatly to the world economy in general and countries in particular. Tourism has the fastest growth rate (9% of GDP), creating many jobs for the society (attracting 8% of the workforce). In 2010, the global tourism industry created more than 235 million jobs, equivalent to about 8% of all jobs (direct and indirect). That’s equivalent to one in every 12.3 jobs from tourism (ILO, 2012). In 2019, Vietnam’s tourism welcomed over 18 million international visitors (up 16.2%), serving 85 million domestic tourists (up 6%). (General Statistics Office, Vietnam). Tourism attracts over 2.5 million employees, of which 860, 000 are direct workers, with 45% trained in tourism, 35% trained in other specialties, and 20% untrained. The tourism industry needs human resources to restore operations in the new situation, especially in the recovery period after COVID-19. Actively welcoming the wave of opening up and recovering tourism, the tourism industry in provinces and cities across the country is aggressive recruitment announcements. At the same time, the locality cooperates with businesses to organize retraining and retraining of human resources in professional qualifications, foreign languages , and soft skills for employees. However, instead of sticking with tourism following COVID-19, many workers actively sought new employment. Aside from persons of working age, attracting senior laborers is also a viable option. To address the labor crisis, the elderly’s work in small and medium businesses should be reincarnated as a high-quality job (Yoo, 2020). On the other hand, human resources are one of the variables that contribute to the development of sustainable local tourism. In terms of establishing steady jobs for labor, sustainable tourism has the opposite effect (Nguyen et al., 2020).

Provinces in the southern Red River sub-region have an area of about 4, 600 km² and a population of 4.6 million people. There are five biodiversity hotspots worth preserving. Outstanding global biodiversity has a significant impact on humanity’s life. They have been recognized as the world’s first Biosphere Reserve in the Red River Delta of Vietnam under the Convention on Educational Scientific and Cultural Organization (UNESCO) since 2004. There are low-lying plains, coastal plains, and hilly and semi mountainous landscapes in these locations. Because the seashore stretches for 142 km, the southern Red River Delta offers a diverse range of natural scenery and tourism values (beaches, historical sites, unique landscapes). As a result, this is a popular tourist attraction for both domestic and international visitors. These provinces have been promoting the benefits of tourist development in recent years and have seen spectacular outcomes. The South Red River sub-region created 18, 000 jobs for employees in 2011, with 6, 587 of them being direct positions. The South Red River sub-region received 9.9 million tourists in 2019. (900, 000 international arrivals). More than 40, 000 employment have been created as a result of the enormous number of visitors (14, 658 direct employees).

Summarizing data from the Department of Statistics of the provinces in 2019 and the Department of Tourism (2019), in the period 2005–2019 (Table 2), the number of laborers for tourism in the southern Red River sub-region increased sharply. In 2005, this force had 2, 143 people; by 2019, it had risen to 14, 658 people.

Table 1 shows data from the Department of Tourism (2019) as well as the Tourism Departments of these three provinces (2019). Year after year, the number of tourism employees in the southern Red River sub-region rises dramatically. In 2005, there were 2, 143 individuals, and by 2019, there were 14, 658 people (an average increase of 15.44%). According to the provinces’ Department of Tourism (2019), the number of well-trained and professional tourism workers remains low, and the quality of tourism worker training remains limited. The majority of employees have not met the requirements for professionalism, management skills, communication, and service quality. Tour guides, in particular, are in short supply (14.5 percent have master’s or university degrees, 28.3 percent have graduated from colleges or intermediate schools, and 40.1 percent are untrained). Many of the trained workers have not had adequate training in tourism and have instead received training in other fields such as economics, finance, banking, and foreign languages. In 2016, Thai Binh had 34 professional guides out of a total of 3, 148 employees with 570, 000 visitors, whereas Nam Dinh has a team of professional guides of roughly 40 persons. If tourism connects provinces and localities, the number of thin guides is likewise a major force constraint.

Table 1: Tourism Workers in the Southern Red River Sub-Region 2005–2019

Source: Departments of Tourism of the Provinces.

The research objectives of this study are:

1. Identify and analyze the factors affecting the employment decision of tourism workers in the southern Red River sub-region.

2. To suggest recommendations for the development of key tourism development in the southern Red River sub-region (Vietnam).

2. Literature Review

Tourism is considered a labor-intensive activity, and by its nature, its multiplier and spillover effects are expected to be higher than in other sectors. Furthermore, this activity creates jobs of all levels and abilities, as well as a greater degree of competition. The spillover effects of tourism manifest in the wealth of tourists which in turn increases demand for local goods and services, either by direct or indirect spending (Gómez López et al., 2019). Therefore, jobs in the tourism industry are also very diverse and spread when serving tourists.

In the same opinion, Habibi et al. (2018) pointed out that the tourism industry can become a long-term target of economic policy, with the potential to increase employment and growth, by (1) Creating greater efficiency and economies of the world base the scale of goods and services, on customer demand; (2) Send signals to the market about the entry of new entrants, creating a positive impact on goods and services; and (3) Competition and more consumer choices can improve quality of life.

Ladking (2011) identified that tourism has been on the economic agenda since the 1980s. The author finds that the majority of studies on the tourism-employment relationship are analyses of the effects of tourism. Tourism activities generate income and wages. From there, studies evaluate the economic benefits that tourism has brought to destinations and tourism development. The results of the aforementioned studies can be used in the design of industrial policy strategies and decision-making. Similarly, Tian and Guo (2021) showed that income and welfare disparity between formal and self-employed workers increased by 17.4% between 2010–2013 and 2015, while income and welfare disparity the profit between formal and informal workers decreased by 16.4%. Disparities in income and benefits are important factors determining employment in the industry.

Gómez López et al. (2019) suggested that public policy promotes balanced economic development, necessitating a thorough examination of the tourism industry’s determinants and impacts. The research looked at elements directly linked to tourism development, as evidenced by the growing need for ancillary services. Also noted is the relationship between tourist destinations and tourist features such as geography, nature, and culture. Public policies that affect entire sectors in regions, provinces, or districts, according to Castillo et al. (2017), can account for a significant amount of local government spending. The study looked at the long-term influence of development policies on employment in the province of Salta (Argentina), finding that over ten years, these policies had an average yearly impact of 11% (for hotel employment), with a total impact of 1376 formal jobs in the tourism value chain. The authors also find that this growth is not due to the costs of other sectors but to the impact of tourism development policies that have created positive spillovers across sectors. For each job created in the tourism value chain, an additional job was created in the rest of the provincial economy, resulting in a total of 2750 formal jobs created.

According to Kajenthini (2019), the tourism business can contribute to positive economic development in a number of ways, including increased gross domestic income, job opportunities, national income, and international trade. Most governments, including the Sri Lankan government, have viewed tourism as the most promising industry as a possible source of income and jobs in recent years. The study found a long-term association between tourism and job creation and found that the absence of a lasting relationship between the two indicators would not determine job creation in the long run. Furthermore, the Granger causality test is used to investigate the short-run relationship, and it confirms the existence of a one-way causal relationship between tourism and job creation showing that the tourism industry of Sri Lanka will create huge jobs for local workers.

Infrastructure and technology increasingly have a great impact on employment in the tourism industry. Janta et al. (2011) examined how migrant workers’ adaption to society is influenced by their employment in tourism and their workplace experiences. In the tourism business, cooperation, promotion, and labor exchange help to develop labor mobility. It then illustrates the employees’ working decisions as they adjust to their new environment. Modern technical facilities are commonly used in industries in Melián-González, and Bulchand-Gidumal (2020). Using data from hotels in Spain, France, Germany, and Europe as a whole, this study showed that the amount of human labor required has reduced over the last ten years. This tendency is particularly noticeable in high-end hotels, and it indicates a decrease in human labor in the hospitality business.

David et al. (2014) developed a workforce development strategy that addresses all of the important factors that influence how individuals fit into a specific job in a specific organization at a specific location. The potential for tourism development in a tourist destination is a factor to be considered when deciding on the employment of workers. The application of this model is intended to enhance research programs and practical implications for meeting the workforce challenges of tourism organizations, associations, and destinations, especially in remote areas.

Kadiyali and Kosová (2013) using data from 43 US metropolitan statistical regions for the period 1987–2006, analyzed the impact of tourism capital flows – measured by the number of hotel rooms sold – on employment over 22 years. non-hospitality industry. Realize statistically and economically significant impacts – 100 extra rooms sold every day for a year create between 2 and 5 new jobs per non-hospitality industry in that area. Cross-sectoral subsample analyzes indicate that construction, retail, healthcare, professional, and engineering services are among the biggest beneficiaries of this spillover. The cooperation and promotion of tourism development with other industries and other tourist destinations is a factor considering the employment of workers.

3. Data and Methodology

3.1. Data Collection

After a pilot study, the author interviews ten employees working in the private tourism industry using convenience sampling, a type of non-profit sampling in which people are sampled simply. This method makes it easy to collect data because each observation in the population has a different chance of being selected. Therefore, we modified the validity of the preliminary questionnaire and adjusted the scale accordingly. In this study, quantitative research is carried out using SPSS software, and a 5-point Likert scale to measure the values of observed variables.

To produce the sample size, according to Slovin (1960) and Tabachnick and Fidell (1991), the minimum sample size should be formulated as follows:

n ≥ 8m + 50

In which,

n is the minimum sample size,

m is the number of independent variables,

In this research, we have six independent variables and a dependent variable; therefore, the minimum sample size is 8 × 6 + 50 = 98 observations.

In another study by Hair et al. (1998), the optimal sample size needs a minimum of five times the number of questionnaires, as follows:

n ≥ 5m

In which,

n is the minimum sample size,

m is the number of questionnaires,

In this study, there are six scales with 36 observed variables, so the minimum sample size is 36 * 5 = 180 observations. Thus, we choose a sample size of 200 observations. As a result, Consistent with the research purposes of this study, a questionnaire-based survey was conducted among the target population.

This research is done based on the descriptive method of research. The term descriptive research refers to the type of research question, design, and data analysis along with descriptive statistics, while inferential statistics try to determine the cause, solution, and effect. The respondents were asked to fill out the questionnaire and rate the importance of the items based on a five-point Likert scale. The selection of the sampling units was left primarily to the interviewer.

This study was carried out based on the descriptive research method. The term descriptive research refers to the type of research question, design, and data analysis along with descriptive statistics, while inferential statistics attempts to identify causes, solutions, and outcomes. Respondents were asked to fill out a questionnaire and rate the importance of items on a five-point Likert scale. The selection of sampling units is mainly left to the interviewer.

Primary data was collected through a prepared questionnaire to collect responses. With this data, the authors will conduct an index analysis to find the mean value of each variable and thereby determine the positive and negative effects of each variable on tourism employment decisions in the subregion south of the Red River.

Secondary information has been collected on an annual basis from various sources such as the yearly reports taken from the website of the Ministry of Vietnam, publications of world trade organizations, different research papers, and surveys of the author.

3.2. Research Framework

Based on the survey of related documents as well as previous studies, we propose a research model as shown in Figure 1.

Figure 1: Proposed Research Model

3.3. Research Model

Numerous empirical studies on employment decisions have been analyzed by Tian and Guo (2021) Kajenthini (2020), Melián-González and Bulchand-Gidumal (2020), David et al. (2014), Nguyen and Nguyen (2020), and Nguyen et al. (2020). In this study, we revise the model for the context of the southern Red River subregion, Vietnam, the estimate can be written in the following equation:

DE = β₀ + β₁IN + β₂WE + β₃POL + β₄CO + β₅EDU + β₆POT + u_i

In which IN, WE, POLM CO, EDU, POT, are independent variables, including Working conditions, Welfare, Tourism Development Policy, Cooperation and Promotion, Educa- tions, and Potential for Tourism Development.

DE: Employee’s employment decision.

Unit is the error term.

4. Results and Discussion

4.1. Descriptive Statistics

Data was collected from about 200 questionnaires; the remaining 193 questionnaires are valid for analysis on filtering out the unsatisfactory tables. Descriptive statistics of the data are presented in Table 2.

Table 2: Information of the Respondents

4.2. Scale Reliability

Scale reliability is the degree to which the measure of a model is consistent. According to the results of Cronbach’s Alpha, all coefficients of Cronbach’s Alpha > 0.6, indicating that the scale is suitable for exploratory factor analysis (EFA) in the next analysis (Table 3).

Table 3: Scale Reliability

4.3. Exploratory Factor Analysis (EFA)

We have six independent variables with 36 observed variables. The EFA analysis is presented in Table 4. For the independent variables, the KMO value is 0.916, which ranges from 0.5 to 1, so the analysis is acceptable. In addition, the cumulative variance of the six extracted factors is 69.225% and greater than 50%. All six factors satisfy the condition with an eigenvalue of 1.325 and greater than 1. For the dependent variable, the KMO value is 0.853, ranging from 0 to 0.5 to 1, satisfying the suitability of factor analysis. In addition, the extracted cumulative variance is 68.002% and greater than 50%, and the qualifying factors with the eigenvalue factor are 3.681 and greater than 1. Therefore, the results are acceptable.

Table 4: EFA Analysis

4.4. Hypothesis Testing and Discussion

The study’s regression is shown in Table 5. Multiple linear regression analysis was performed using SPSS 22 software. Table 5 shows that the adjusted R2 value is 64%. It means that the independent variables in the model can explain 64% of the variation of the dependent variable on employee performance, the rest (36%) is due to other variables, and random error was not found. in this study. In addition, Table 5 also describes the policy of tourism development (POL), education and training (EDU), and tourism cooperation and promotion (CO) that have an insignificant impact on the employment decision of tourism workers. The results show that tourism development, education, training policies, and tourism promotion cooperation do not affect the working decision of tourism workers in the southern Red River sub- region, Vietnam.

Table 5: Results of Multiple Linear Regression Analysis

In this study, we found that three factors have a positive and significant impact on employee performance, including working conditions (IN), welfare (WE), and potential for tourism development (POT). Furthermore, the factors with the strongest impact are WE, IN, and POT, respectively.

Table 5 also shows that the VIF is less than 10, which means that multicollinearity may not be present in this study. The regression would be written as follows:

In which, Unstandardized coefficients

DE = 0.242 + 0.342IN + 0.379WE + 0.058POL + 0.022CO + 0.029EDU + 0.221POT + u_i

Standardized coefficients:

DE = 0.312IN + 0.314WE + 0.065POL + 0.025CO + 0.031EDU + 0.240POT + u_i

Table 5 shows that welfare has the most positive impact on employment decisions in the tourism industry in the southern Red River sub-region. That means great benefits such as salary, insurance, labor safety, food hygiene and safety, and social security have contributed to employees’ decision to work in the tourism industry in the state. south of the Red River. Where the tourism industry can bring more positive energy to workers, they are willing to decide to work and stick. This finding is consistent with Elias and Scarbrough (2004), employees who decide to work somewhere, are subject to significant changes in wages, bonuses, and benefits in the industry.

The working conditions include social characteristics and physical and technical conditions that may appear around workers. Modern and improved technical facilities will help employees work safer and more productively. In this study, it is clear that the working conditions are becoming an important role in deciding to work there. More specifically, an increase of 1 unit in the working conditions can positively improve the employee’s decision to work by 0.342 units. This is consistent with previous studies by Diamantidis and Chatzoglou (2019), who confirmed that the working conditions have a positive and significant impact on the employment decision of the employees.

The development potential of the tourism industry is also a factor that workers are interested in. The potential for tourism development in tourist spots is an opportunity to attract investment and attract labor. The more the tourism industry has great development potential, the more job and investment opportunities there are. The tourism potential here is the tourism products that the tourist destination can turn to in the future to attract tourists. There may also be new or expanded tourist attractions. Table 5 shows that, in the case of the southern Red River sub-region, Vietnam, the potential for tourism development is an important contributing factor to the employment decision of workers in the industry. In particular, a one-unit increase in development potential can positively influence 0.221 units of working decisions. This is consistent with a previous study by David et al. (2014).

5. Conclusion and Recommendations

Attracting labor for the tourism industry, especially high quality workers, requires the tourism industry to innovate, especially in the current difficult context (epidemic, competition...). Tourism development needs to be focused and directed towards places that can exploit and create specific and competitive products, creating a brand for tourism in the southern Red River sub-region. From there, the sub-region south of the Red River can attract labor. Although the tourism industry has faced numerous difficulties from the COVID-19 epidemic, there have been many bright spots in policies and guidelines, such as opening airports and welcoming international tourists.

Based on the characteristics of the tourism industry as well as the specific conditions of the provinces in the southern Red River sub-region, tourism development should focus on the following contents.

Firstly, strengthen the development of tourism service businesses and support services in the direction of quality, prestige, and efficiency. Support services are the factor that has the strongest impact on attracting tourists to the southern Red River sub-region. Provinces should approve the establishment of large-scale tourism businesses (maybe joint ventures, associations, cooperation) both to attract investment and to give other businesses the motivation to develop. Focus on maintaining and developing a group of small and medium-sized enterprises to create an even network of tourism services, create jobs, and contribute to hunger eradication and poverty alleviation in the locality. Promote and create conditions for tourism businesses in the province to expand links and become strategic partners of large domestic and international tourism businesses. Since then, businesses have aimed to exploit brands, tourism markets, management experience, and advanced tourism operations. The government creates favorable conditions for tourism and service businesses in the province to associate and cooperate with other businesses to develop specific tourism products. Improve both quantity and quality of tour operators in the province. Travel businesses actively and actively link different types, zones, spots, and routes of tourism.

Secondly, developing specific tourism products is associated with diversifying tourism products. The biggest strength of tourism in the southern Red River sub-region is cultural tourism, especially cultural and spiritual tourism. Therefore, it is necessary to consider cultural values as the root and driving force for tourism development and to promote research and cultural value systems. The provinces need to do well in preserving and promoting the cultural values of the Red River Delta region, continuing to spread and strongly promote the value of the intangible heritage of humanity and the relics and cultural heritages that have been recognized by the Red River Delta— recognized at international, national, and provincial levels— strengthening socialization, attracting the participation of all economical sectors and local communities in the work of protecting, restoring, embellishing, and promoting national cultural identity (such as developing Traditional craft villages, restoration and maintenance of traditional festivals, community activities, and developing of clubs of Cheo singing, folk performances, etc.) to develop various types of special cultural tourism products show.

Thirdly, promote and manage the value of tourism resources. The provinces in the Red River sub-region have many different potentials to exploit and develop this type of tourism. The implementation of activities to promote the value of tourism resources effectively and sustainably is a question not only for the tourism industry but also for many other related sectors. Besides, the provinces in the Red River sub-region always preserve and promote the good customs and traditions of culture and history to the next generation. Promoting intangible cultural values such as Hat Cheo, Hat Chau Van, and ancestor worship is the responsibility of the people, especially to help the young generation realize and be proud of the values left by their ancestors. Along with exploiting tourism resources, local tourist spots must also be closely protected. The management here requires to be organized reasonably to ensure the preservation of resources and bring the greatest benefits to the people. The tourism resource co-management model is a suitable model for the protection and development of resources at tourist sites in the provinces. Along with exploiting tourism resources, local tourist spots must also be closely protected. The management here requires to be organized reasonably to ensure the preservation of resources and bring the greatest benefits to the people. The tourism resource co-management model is a suitable model for the protection and development of resources at tourist sites in the provinces.

Finally, improve tourism management capacity and efficiency. Improving management capacity and efficiency is a regular solution. All solutions can only be implemented when management is effective, so management capacity must reach a certain level. To do this, the following issues need to be resolved:

Innovating thinking, building a new, modern and objective tourism model. Determining the basic characteristics of the model will be the basis for determining the organizational structure, functions, and powers of various levels of government in tourism management.

Accurately determine the functions, tasks, powers, and contents of State administrative management at all levels of tourism management.

Improve the quality, capacity, and professional knowledge of staff in the administrative apparatus of tourism management (Do et al., 2021).

Institutional improvement: to increase the role of government at all levels in tourism management – a necessary condition for sustainable tourism development.