Question

Associations between Quantitative, Qualitative Job Insecurity and Well-being

Research questions

De Witte et al. (2010) investigated the association of employee’s perception of quantitative and qualitative job insecurity with job satisfaction, and psychological distress in the Belgium banking sector.

Job insecurity is defined as the employees’ concerns about their work-related future. There are two kinds of job insecurities, the quantitative job insecurity and the qualitative job insecurity. The quantitative job insecurity is about the threat to the continuation of the job in the future. The qualitative job insecurity is about threat to the various valued aspects of the job, such as job content or working conditions.

Data collection and respondents

In total, there were 69,000 employees working in the 63 Belgian banks affiliated to the sector’s joint industrial committee in 2001. As questioning all employees would be too expensive, the researchers decided to survey a sample of 15,000 employees (roughly 21%).

All the 63 banks participated in the survey. About 21% of employees in each bank were invited to participate in the survey. Within each bank, the respondents were selected at random with no particular quota for gender, age or employee level. The survey was based on addresses which had been provided by the banks (name, language, address) and each randomly selected employee received a personalized envelope through regular mail, sent to him/her by the employer. The completed questionnaire needed to be returned (free of charge) through the internal post within each bank. The researchers travelled to each bank to collect the completed survey.

The sample was representative for employees in the banking sector, however, not for the total working population. More men (58.5 percent) than women (41.5 percent) participated. About two in three respondents were between 35 and 44 years old or between 45 and 54 years old, while about one in four was between 25 and 34 years old. Only a minority (4 percent) was younger than 24 or older than 55. Most respondents had an education beyond high school (63.9 percent), had partners with an income and children (72.4 percent), and worked full-time (85 percent). There were about as many white-collar workers (54.4 percent) as executives (45.6 percent).

Measures

Quantitative job insecurity was measured with four items developed by De Witte (2000) on a scale from 1 (strongly disagree) to 4 (strongly agree). Sample items were “I feel insecure about the future of my job”’ and “I am sure that I will be able to keep my job” (reverse coded). Reliability (Cronbach’s alpha) equalled .89.

Qualitative job insecurity was measured with ten items from the 17 item measure that was originally proposed by Ashford, Lee, and Bobko (1989). These job features concerned four broad dimensions previously distinguished to describe the various characteristics of a job: job content (autonomy, skill utilization, and specific tasks), working conditions (workload and quality of working conditions), employment conditions (wage, working hours, and opportunities for promotion), and social relations at work (relations with colleagues and supervisors, respectively). Respondents had to indicate whether each of the job features would likely improve or deteriorate in the near future (1 = strongly deteriorate; 5 = strongly improve). We recoded the items so that a high score reflected qualitative job insecurity. Cronbach’s alpha equalled .87.

Job satisfaction was measured with one item: “Overall, how satisfied are you with your current job?” (1 = very dissatisfied; 5 = very satisfied).

Psychological distress was measured with the 12-item version of the General Health Questionnaire (Goldberg, 1978). A sample item was “Have you recently lost much sleep over worry?” Responses varied from 1 (“less than usual”) to 4 (“much more than usual“). Reliability (Cronbach’s alpha) was .89.

Control variables. The following social demographics and work-related factors were included: gender (0 = men; 1 = women), age (1 = 18–24; 2 = 25–34; 3 = 35–44; 4 = 45–54; 5 = 55+), education (0 = no education beyond high school; 1 = education beyond high school), extra income (0 = no partner with extra income; 1 = partner with extra income), children (0 = no children; 1 = children), occupational position (0 = white-collar worker; 1 = executive), working hours (0 = part-time; 1 = full-time). The demographics were used as control variables in data analysis.

Instructions for answering the questions

Use at least four academic sources in English to answer the questions. The sources can be books or peer reviewed journal articles or a combination of both books and peer reviewed journal articles. The academic sources as well as responding to the questions will be around 2000 words in total.

Q1: Sample size

The sample size for this study is fifteen thousand employees selected from a total of 69,000 bank employees (about 21% of the employees). Is a sample of this size necessary? Give your reasons.

Q2: Sampling method

What is the current method of sampling? What are the advantages and disadvantages of the current sampling method?

Q3: Measures of variables

Give your comments on the reliability and validity of measures of the variables.

Q4: Collection of data on social demographics

The purpose of this research is to find the associations between quantitative and qualitative job insecurity and well-being. However, data on variables such as gender, age, education level, extra income were also collected. What is the purpose of collecting data on variables such as gender, age, educational level etc.?

Q5: Research design

What research design is used for current research? What are the positive and negative side of the current research design?

References

Ashford, S. J., Lee, C., & Bobko, P. (1989). CONTENT, CAUSE, AND CONSEQUENCES OF JOB INSECURITY: A THEORY-BASED MEASURE AND SUBSTANTIVE TEST. Academy of Management Journal, 32(4), 803-829. doi:10.2307/256569

De Witte, H. (2000). Arbeidsethos en jobonzekerheid: meting en gevolgen voor welzijn, tevredenheid en inzet op het werk (Work Ethic and Job Insecurity: Measurement and Consequences for Well-Being, Satisfaction, and Performance at Work). In van groep naar gemeenschap, ed. R. Bouwen, K. De Witte, H. De Witte, and T. Taillieu, 325–350. Leuven: Garant. Goldberg, D. P. (1978). Manual of the General Health Questionnaire. Windsor, UK: NFER-Nelson.

De Witte, H., De Cuyper, N., Handaja, Y., Sverke, M., Näswall, K., & Hellgren, J. (2010). Associations between quantitative and qualitative job insecurity and well-being: A test in Belgian banks. International Studies of Management & Organization, 40(1), 40-56. doi:10.2753/IMO0020-8825400103

Answer 1

Q1 Sample size

21% example size demonstrates a room for give and take of about 2.5% with a certainty interim of almost 99%. Presently, when we choose a test size, these two components influence the precision of information. Room for give and take demonstrates the positive and negative deviation from the genuine event. This implies the 2.5% is the deviation that is likely conceivable from the discoveries and the real situation on the ground. This is a decent incentive to have. Truth be told, numerous explores think about 5% room for mistakes. The lower the number, the more precise is the outcome. The following is the certainty interim (level). 99% certainty level implies that 99% of the populace is probably going to fit into the discoveries from the overview. Here the higher qualities shows better discoveries from studies. In this manner 99% is a decent number and 15000 respondents will probably give another precise discoveries.

As a rule, lower esteems, for example, 5% room for give and take and 95% certainty interim is thought of. In any case, right now need to get that while the populace is 69000, it is spread across 63 banks. This implies there are different components that can affect the reactions of the individuals being over viewed. This carries us to another couple of key contemplation that should be recalled while arranging an overview. They are noteworthiness level, impact size, and force level. These three elements impact the effect of the example on the whole populace. In the event that we had taken a littler example size, there could be plausibility that specific banks would not be spoken to appropriately. That would likely give an outcome that is unjustifiable.

Subsequently, taking everything into account, an example size of 15000 respondents is a decent number.

Q2 Sampling technique.

The present inspecting strategy was arbitrary examining. The case brings up that the overview was sent to representatives at irregular without thinking about any of the socioeconomic. The motivation behind arbitrary examining is to accomplish an outcome with the least predisposition. Be that as it may, there are a few weaknesses also. The points of interest and disservices are.

Favorable circumstances

Less possibility of predisposition: When tests are chosen in irregular, the odds of inclination is less. This is on the grounds that an arbitrary example speaks to the whole populace.

Uniform choice: Theoretically, arbitrary example gives equivalent possibility of determination with regard to the whole populace.

More straightforward: Creating and leading an irregular example is less mind boggling than different techniques since it doesn't require predefined arrangement or framework.

Discoveries are uniform: Since the testing is arbitrary, the discoveries from these studies can be pertinent to the whole populace.

Disservices

Earlier information disregarded: Random testing is a fair however, on the off chance that a specialist has an earlier information on a predisposition, even that is overlooked. This implies the earlier data might be squandered.

Requires larges test size: In request to have exact discoveries, the example size should be huge. This puts forth the attempt more and the multifaceted nature may emerge contingent upon the sort of research.

May not delegate of the populace: If there are gatherings of various arrangement of populace being over viewed then there is a high chance that the finding may not precisely speak to the whole populace.

Profoundly talented scientists required: Random testing gives a ton of irregular information. This requires an able specialist who can evaluate this information, bunch them, examine them and afterward show up at a finding.