Sampling Options

In Table 4.1 below, three different data collection options were considered in order to achieve thesis objectives.

Table ‎4.1: Sampling Options, with Advantages and Disadvantages of Each Option

Sampling Option Advantages Disadvantages

1.) Geographical home locations

Catching expatriates who were away from work because of sickness.

There is no database that locates expatriate living areas.

Expatriates can talk freely about their participation in a natural, free environment

Very difficult to capture expatriates alone as they live in the same neighbourhoods as the citizens.

Away from work environment pressure

Expatriates work long hours, which makes it difficult to reach them even during weekends. This approach is impossible in a large city like Riyadh. 2.) Gathering areas, where most expatriates meet mainly during weekends

Easy to conduct Might miss the population of the expatriates who do not come to these gathering areas for different reasons

Expatriates will likely feel they have freedom of speech

Expatriate gathering areas are dedicated for very specific nationalities, therefore difficult to catch other nationalities.

33

The economic sectors have been defined in table 4.4 based on International Standard Industrial Classification of Economic Activities (ISIC) as will be illustrated in section 4.10

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Sampling Option Advantages Disadvantages

3.) Expatriate employees’ workplaces

This approach ensures fair representation of all expatriates considering their company’s size, and economics sector

Sick workers cannot be captured by this method since they are away from work.

This method guarantees sample representation regardless of the worker’s job characteristics

Refusal of both employers and employees to conduct the interview during working hours as workers have other things to do.

Taking a proportional sample from all expatriates according to their economic sector and company size ensures accurate data analysis for some of the study main objectives (i.e. based on job characteristics)

Fears of recrimination against participants from employers, may lead to misleading answers.

This approach is the easiest way to target the expatriate population considering their long working hours.

This method helps measure some of the thesis objectives such as employers’ characteristics (companies’ size and economic sector).

After thorough evaluation of the different sampling methods, the third option was selected as it was much more advantageous than the others (per Table 4.1). Thus, the survey forms were distributed to workers in their workplace after obtaining approval of the company owner and/or General Director of the company.

To collect data from the employee within the workplace, we anticipated some difficulties. Table 4.2 below summarizes the expected difficulties and ways to overcome them.

Table ‎4.2: Expected difficulties to collect data from the work place and ways to

overcome them

Difficulty Solution

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Difficulty Solution

method since they are unlikely to be at work.

accommodation.

Refusal of either employers or employees to participate in the interview during working hours due to work commitments.

Interviews were conducted during break times and during bus trips to and from the workplace. Interviews were scheduled ahead of time at the employee’s convenience. This kind of arrangement was essential for large employers. However, this arrangement was difficult in some of the economic sectors, particularly Construction. Therefore, some interviews were conducted in workers’ accommodation due to an unfavourable workplace setting.

Fears of recrimination against participants from their employers may lead to misleading answers.

The credibility of the research sponsor was emphasized during conduction of the study, including confidentiality of the participants’ opinions and their rights (as stated clearly in the consent form).

It was also expected that company directors and employees would be hesitant to participate in the survey. In order to encourage and give employers and workers confidence in their participation and to reduce participants’ anxiety when answering the questionnaires, the following steps were taken, as outlined in Table 4.3 below:

Table ‎4.3: Actions Taken to Increase Employer and Employee Confidence

in the Impartiality of the Research

Employers Employees

Official letters and identification cards from the King Abdullah International Medical Research Centre (KAIMRC) (research sponsor) were provided to promote confidence that the study was official and the employers’ contributions would be for research purposes only.

Official letters and identification cards from the KAIMRC (research sponsor) were provided to provide confidence that the study was official and employees’ contributions would be for research purposes only.

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Employers Employees

Due approval from the company owner and/or General Director was sought prior to communicating with employees.

Emphasis on confidentiality of the participants’ identity, that answers and any related information would not be announced or linked to the participants, even to their employers. They were also notified of their right to withdraw their participation at any time.

Emphasis on the confidentiality of the participants’ identity, that answers and any related information would not be published or linked to the participants.

Research Assistants administering the survey were selected from the same dominant nationalities and languages of the private sector employees, to ensure that participants understood the survey in their mother language.

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Sampling Development Options:

How many individuals must be selected from each company?

If a large company is selected (e.g. a company with more than 3,000 workers), how many employees must be selected from this company to be representative? Two approaches were considered:

Firstly, we could select large samples from each company. This method has the advantage of covering different workers with different positions or responsibilities, i.e. managers, technicians, labourers. However, this method restricts the number of companies selected from each economic sector and restricts the variation in company sizes. For example, if a large sample was selected from the mining sector, only one large company might be chosen. Furthermore, this approach might minimize the selection of companies of other sizes such as a sample from companies with 1-9 employees.

Secondly, to select a limited number of workers and increase the number of companies in the study. Since the cost of health insurance is borne by employers and not the workers, studying many different companies is more valuable than selecting more workers in each company. In addition, since health insurance is linked to renewal of the Iqama residency permit for expatriate workers, the behaviour of the employers with regards to health insurance is vital to the study objectives. Therefore, the minimum number was fixed at 30 employee samples from each company. If the company had less than 30 employees, another company with the correct sample size would be chosen to complete the 30 samples.

Based on the company size, two actions were considered: 1) a company with less than 30 employees, all employees were selected as study participants, and another company selected to complete the required minimum number of employees; 2) a company with more than 30 employees, a maximum of 30 employees was randomly selected from that company’s database.

How many employees must be included in the study?

Figure 4.1 illustrates how the number of employees was calculated. The initial sample size was calculated at 2,920 employees. The samples are proportionately selected and distributed to all economic sectors and company size, accordingly. To do this, the overall sampling fraction was determined by dividing the initial sample size required by the total number of expatriate workers in Riyadh (2,920/2,093,099=0.001395). The overall sampling fraction was then multiplied with the number of employees in each economic sector in order to achieve the number of employees from that economic sector. For example in the

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agriculture sector the total number of employees is 19,070. The sample size from the agriculture sector that is proportional to the total number of employees in this sector would therefore be equal to (19,070 x 0.001395=26.594695). The product is then rounded off to the nearest absolute value.

Within the economic sector, the number of employees was also calculated proportionately in order to calculate the number of employees per company size within that sector. To do this, the sampling fraction within the economic sector was calculated by dividing the sample size in that economic sector by the number of employees in that sector. For example in the agriculture sector the sample size, 27, was divided by 19.070 to compute the sampling fraction within the agriculture sector. Then the sample size according to company size within an economic sector was calculated by multiplying the sampling fraction within the economic sector by the number of employees according to company size within the sector. The data for the number of employees according to company size within an economic sector is extracted from the Ministry of Labour database. The final sample size from each company by economic sector is shown in Figure 4.1 overleaf.

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Figure ‎4.1: Calculating the number of samples for the study

++ - 2,093,099 based from Ministry of Labour database * - for example, Agriculture sector: 19070 employees **-based from Ministry of Labour database

Start

(Initial sample size: 2,920 samples)

To calculate the number of employees per economic sector, first determine the overall sampling fraction: Initial sample size required/ total number of expatriate

workers in Riyadh++ = 0.001395

Compute the number of employees selected from each economic sector:

Number of employees per economic sector* x sampling fraction

To determine the number of employees selected from each company size within economic sector, first calculate

the sample fraction of employees within economic sector:

Sample size per economic sector/ number of employees per economic sector*

To calculate sample size according to company size within an economic sector:

Sampling fraction within economic sector × number of employees according to company size within the sector**

Is the value less than or equal to 30?

Use ‘30’ as the final sampling size Y

N

Use computed value as the final sample size

End (Final sample size: 3,455 samples)

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Table ‎4.4: Calculating the number of Samples/Individuals for the Study

Economic Sector Number of employees per sector Overall sampling fraction Sample from each Econo mic Sector Absolute Value (Sample from each Economic Sector) Sampli ng fraction within Econo mic Sector Company Size Number of employees per company size within Economic Sector Sample Final Sample 1. Agriculture 19070 0.0013946 26.5946 95 27 0.00141 5836 <10 4422 6.2606676 30 10-24 1363 1.9297354 30 25-49 1322 1.8716876 30 >=50 11963 16.9372154 30 2. Mining 2601 0.0013946 3.62731 4 0.00153 787 <10 125 0.0015379 30 10-24 179 0.0015379 30 25-49 106 0.0015379 30 >=50 2191 0.0015379 30 3. Manufacture 187762 0.0013946 261.849 67 262 0.00139 5384 <10 35130 49.020402 50 10-24 21154 29.5182916 30 25-49 22550 31.46627 30 >=50 108928 151.998131 152 4. Electricity 1401 0.0013946 1.95381 06 2 0.00142 7552 <10 70 0.099932 30 10-24 34 0.0485384 30 25-49 177 0.2526852 30 >=50 1120 1.598912 30 5. Construction 971159 0.0013946 1354.36 17 1354 0.00139 421 <10 49765 69.3828607 70 10-24 51920 72.3873832 72 25-49 64747 90.2709149 90 >=50 804727 1121.95843 1121 6. Trade 541829 0.0013946 755.625 44 756 0.00139 5274 <10 88902 124.042649 124 10-24 72138 100.652276 101 25-49 63390 88.4464189 89 >=50 317399 442.858572 443 7. Transport 35137 0.0013946 49.0014 58 49 0.00139 4541 <10 8116 11.3180948 30 10-24 1746 2.43486859 30

Page 103 Economic Sector Number of employees per sector Overall sampling fraction Sample from each Econo mic Sector Absolute Value (Sample from each Economic Sector) Sampli ng fraction within Econo mic Sector Company Size Number of employees per company size within Economic Sector Sample Final Sample 25-49 2745 3.82801505 30 >=50 22530 31.4190087 31 8. Finance 60464 0.0013946 84.3220 58 84 0.00138 9256 <10 5108 7.09631965 30 10-24 4532 6.29610819 30 25-49 4786 6.64897922 30 >=50 46038 63.9585677 64 9. Personnel services 230582 0.0013946 321.565 71 321 0.00139 2129 <10 40979 57.0480543 57 10-24 19418 27.0323609 30 25-49 18349 25.544175 30 >=50 151836 211.375299 211 10. Others 43094 0.0013946 60.0981 54 60 0.00139 2305 <10 8128 11.316655 30 10-24 8049 11.2066629 30 25-49 6956 9.68487358 30 >=50 19961 27.7918001 30 Total 2,093,099 0.0013946 2,920 3,455

Database Sources Selection

There were three main databases available for construction of the sampling frame. The Ministry of Labour database was selected because its database is updated every two years, whereas the Ministry of Commerce’ database is only updated every five years. The Organization of Social Insurance (GOSI) also has a database for all companies that register with them only and it is updated annually. However, not all companies in the private sector have registered with GOSI (Al-Wehibi, 2009). Therefore, the Ministry of Labour’s database was selected as its database updating cycle is shorter than that of the Ministry of Commerce, and registration to its database is compulsory for all private sector companies. After categorizing the companies based on their size (less than or equal to 10 employees, from 11 employees to 24 employees, from more than 24 employees to 50 employees, and

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more than 50 employees), Table 4.4 illustrates the categories of the companies based on their economic sector and size.