Job Insecurity And Well-being: A Study On Belgian Bank Employees

Research questions

This size of the sample is required due to the high amount of samples are highly proximate to the population. Moreover, the primary objective of implementing the high amount of sample is to gather the detail and wide category of information through a sample of the population. A researcher has targeted larger size of the sampleto develop some assumption regarding the research study. The size of the sample offers more reliable results with finest quality and validity, but, there is a need for a large extent of cost with time (Mackey, and Gass, 2015).The larger size of the sample is more essential for obtaining the results amongst variables that are considerable distinguish.For the qualitative investigation, the purpose is to reduce the chances of addressing failure. A high amount of sample includes more people because there is the possibility of obtaining larger prospect data and developsan image for appraisal. Moreover, the larger size of sample depicts theinhabitants and restricts the impact of incredible scrutiny (Taylor, Bogdan, and DeVault, 2015).

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Probability sampling is the existing sampling technique in this investigation. This technique depends on the evidence that each respondent of the large population hasrecognized and equal chances of being the selection. In this investigation, a simple random sampling technique has chosen as population member are associated with each otherin terms of the considerable variable (Lewis, 2015).

Advantages of using Random Sampling

Random sampling allows a researcher to obtain the evaluation of facts and figures that are collected within the lower margin of error. It restricted that sampling should base on specific criteria and enables an investigator to select the feasible process of sampling. The whole process relies on the randomized process which depicts the whole population. It also permits the facts to provide the precise insight regarding specific subject concern (Glesne, 2015).

It is also determined that simple random sampling enables each respondent within the targeted field to get identical chances of being selected. It helps to acquire more feasible facts and figures as each respondent has 50/50 probability. It is a process of developing the inherent fairness intothe investigation but, there is no previous evidence with regards to entailingparticipants intothe data collection process. Another advantage of applying a simple random sampling technique is that there is no requirement for particular comprehension with respect to gathered data. This could be beneficial for developing the purpose and objectives in an efficientwith the effective way (Flick, 2015).

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Data collection and respondents

A research can also communicate with workforces who engaged in Belgian banks that are affiliated with joint industrial committee sector in 2001 in spite of understanding the Belgium banking structure. Under the random sampling techniques, a question is asked and then answered by targeted individuals. This technique could be beneficial to review the questions with the particular purpose. A researcher can accomplish the aim with objectives of research because of accomplishing the tasks and gathering the data by implementing the simple random sampling procedure (Silverman, 2016).

Disadvantages of Random Sampling

In this sampling technique, each person should be personally interviewed and reviewed hence the data can be adequately collected. When an individualis in groups, then their responses tend to be influenced by answers of others. Hence, a researcher should deal with each individual on 1 on 1 basis (Ledford, and Gast, 2018). There is need of more resources, time with efficiency as compared to another investigation tool. For this procedure, a high extent of competency is essential for a researcher because it enables them to segregate the applicableand inappropriate data from gathered information. Moreover, in case of lack of competency, consistency in conclusion and presented information may be difficult (Smith, 2015). 

Reliability can be illustrated as the consistency in the conclusion. In the given investigation, more than one individual perceives the conduct of respondents and recorded their data with regards to the concern of research to acquire reliable information (De Witte, et. al., 2010). It could be implemented to measure the pooled data from an individual. While a researcher conducted a survey two times, then their score on two intervals should be consistent. In such way, the test would be dependable (Choy, 2014).

Cronbach’s alpha is a measure that is practiced to determine the reliability and inside stability. It shows the set of gauge or test substances. Furthermore, the reliability of a given measurement defines the extent to which an investigator measuresthe aspects.Cronbach’s alpha is a significant mode to assess the strength of consistency. If the alpha value is .70 then the instrument will be considered as reliable (Dang, and Pheng, 2015).

Validity

Validity is the dependability and credibility of research that demonstrates the authentic outcomes and valid determination of intelligence. The responseis depending on the extent of the researcher to build liaison with participants (Dumay, and Cai, 2015).

The given measure can be used to measure tothe validity of research:

Measures

Internal validity

The mechanism and procedure implemented in the investigation could be used to evaluate what a researcher perceives to measure. For example, as part of a survey on Belgian banks, workforces have shared their views and opinion about the issue of investigation. After the investigation, they are asked how they feel at the time of survey through questionnaire and they haveresponded that it has facilitated me the opportunity to share my views and opinion about research issues (Wiek, and Lang, 2016).

External validity –

The result can be illustrated after gathering information. In order to measure the external validity, there is evidence that the research in different elements can be effective rather than reviewing the research and apply more than one issue. It should also involve people, who are beyond the sample in the investigation to obtain the valid information (Walliman, 2017). 

While information is valid then it should be reliable. In case, a researcher acquires different scores from the survey through a questionnairein each period then the test is not likely to predict anything. However, when the measurement is reliable then, it does not show that it would be valid. For illustration, a researcher can assess the strength very consistently but, it may not valid measure regarding the mechanical and intelligence capabilities (McCusker, and Gunaydin, 2015).

Demographic questions depict the information with regards to features in the sample population like their gender, age, income, residence, education level, ethnicity, and language spoken. The demographic information provides the information regarding participants of research and it is essential to assess whether a person can be selected as a representative sample from a chosen population to illustrate the purpose (van groep naar gemeenschap, et. al., 1978). Moreover, demographics or characteristics of respondents are essential for an investigator as it deals as an independent variable in the design of the investigation. Demographic variable demonstrates the independent variable in the research because it could not be operated (Reynolds, Creemers, Nesselrodt, Shaffer, Stringfield, and Teddlie, 2014). 

The mixed research design can be practiced with the intention of this investigation. This design of investigation incorporates the pooling, evaluating and integrating the qualitative like literature review research with quantitative research like a survey. This design of investigation is applied for using the combined benefits and gain the depth understanding regarding research issue rather than applying another one(Walliman, 2017). Moreover, the quantitative information includes the close-ended information like determining the opinion such as rating scales, behavior like observation checklist and instrument of performance. The evaluation of this set of data involves the statistical assessment in order to determine the score obtaining from checklist and questionnaires in order to respond toeach question of research. The qualitative information includes the open-ended information that a researcher pools via literature review and case study (Neuman, 2016).

Q1: Sample size

The positive side of using a mixed research design

This design of investigation provides the strength that balances the weaknesses of both qualitative and quantitative research. For illustration, the quantitative investigation is weak to understand the context and makes the setting on which people will react. In opposed to this, the qualitative investigation can be demonstrated as inadequate facts and figures because of the possibility of partiality in the discussion made by a researcher. It may create difficulty in terms of explaining the verdicts of the large group (De Witte, 2000). However, at the same time, quantitative designing of investigation does not contain these restrictions. Therefore, it is evaluated that by implementing bothtypes of investigation, the strength of each strategy can reduce the possibilities of weakness from the investigation (Reynolds, Creemers, Nesselrodt, Shaffer, Stringfield, and Teddlie, 2014). 

The negative side of using a mixed research design

There is some unfavorable side of implementing the mixed designing of research. It could be difficult for the researcher. It also takes more time with a largenumber of resources to make strategy and execute this kind of research. It could be difficult to make a plan and implement one method by illustrating the findings of another. It may be unclear that how to deal with the inconsistency that creates in comprehending the findings.  

Another limitation of implementing this design of investigation is that when a researcher determines the qualitative information then it may decline the resilience and depth of qualitative research. It exists because qualitative codes are multidimensional. In opposed to this, quantitative codes rely on the one dimensional and static so, mainly altering the qualitative data to dichotomous variables. This may generate one-dimensional and indisputable facts and figures in research. It is appropriate for a researcher to avoid the degree of qualitative data. But, it could take more time and difficult process as there is a requirementfor assessing, coding, and integrating the data from unstructured to structured facts and figures (Walliman, 2017). 

The key disadvantage associated with this mixed research design is that there is a restriction in statistical gauging qualitative data. Thus, it is illustrated that while qualitative facts and figures are assessed then, it could be chances of weak co-linearity. In addition, it is illustrated that the researcherpractices qualitative information because of reducing their sample size and also it takes less time. There is no requirement to gauge the statistical procedure like evaluating the variance and t-tests. It is a key restriction for this qualitative research design as a researcher may not have sufficient statistical power to support the research. It can be eliminated when a researcher decides to not using mixed designing of investigation (Dumay, and Cai, 2015).

Q2: Sampling method

Sequential explanatory design

In the mixed research design, the sequential explanatory design can be practiced by an investigator. This design incorporates the evaluation of qualitative facts and figures. The primacy is offered to quantitative information and findings are integrated at the time of evaluation phase of the investigation. This type of mixed research design is used to discuss, construe and contextualize the quantitative findings. It can be also practiced to evaluate the potential outcome in more depth via quantitative research (Dang, and Pheng, 2015).   

The positive side of using Sequential explanatory design

The favorable aspect of implementing this design of research is that it is easy to implement as the stagescome into the explicit single stage. This design is easy to illustrate and the gathered data could be easy to make a report (Walliman, 2017). 

The negative side of using Sequential explanatory design

The unfavorable side of implementing this design of investigation is that it requires an extensive time period for transforming all gathered information into two separate phases(Dumay, and Cai, 2015).

Example:

This research study collects the facts and figures with regards to Associations between Quantitative and Qualitative Job Insecurity and Well-being by using the survey through a questionnaire. This survey is done on the high amount of sample size to obtain more depth information associated with the research issue (Dang, and Pheng, 2015).    

Table 1: Research Timeframe for completing the research

Gantt chart illustrates the graphical picture of an action plan that is executed to define how the research practices would be applied phase by phase. It can be discussed as given below:

 

The above time structure evaluated that pooled data is related to research issue and interpretation of data will take a longer time period as compared to implementing other activities (Walliman, 2017).

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.

Choy, L. T. (2014). The strengths and weaknesses of research methodology: Comparison and complementary between qualitative and quantitative approaches. IOSR Journal of Humanities and Social Science, 19(4), 99-104.

Dang, G., &Pheng, L. S. (2015).Research methodology.In Infrastructure Investments in Developing Economies (pp. 135-155). Singapore: Springer.

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).

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.

Dumay, J., &Cai, L. (2015). Using content analysis as a research methodology for investigating intellectual capital disclosure: a critique. Journal of Intellectual Capital, 16(1), 121-155.

Flick, U. (2015). Introducing research methodology: A beginner’s guide to doing a research project. UK: Sage.

Glesne, C. (2015). Becoming qualitative researchers: An introduction. UK: Pearson.

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.

Ledford, J. R., & Gast, D. L. (2018). Single case research methodology: Applications in special education and behavioral sciences. UK: Routledge.

Lewis, S. (2015). Qualitative inquiry and research design: Choosing among five approaches. Health promotion practice, 16(4), 473-475.

Mackey, A., &Gass, S. M. (2015). Second language research: Methodology and design. UK: Routledge.

McCusker, K., &Gunaydin, S. (2015). Research using qualitative, quantitative or mixed methods and choice based on the research. Perfusion, 30(7), 537-542.

Neuman, W. L. (2016). Understanding research. Pearson.

Reynolds, D., Creemers, B., Nesselrodt, P. S., Shaffer, E. C., Stringfield, S., &Teddlie, C. (Eds.). (2014). Advances in school effectiveness research and practice. USA: Elsevier.

Silverman, D. (Ed.). (2016). Qualitative research. UK: Sage.

Smith, J. A. (Ed.). (2015). Qualitative psychology: A practical guide to research methods. UK: Sage.

Taylor, S. J., Bogdan, R., &DeVault, M. (2015). Introduction to qualitative research methods: A guidebook and resource. USA: John Wiley & Sons.

Walliman, N. (2017). Research methods: The basics. UK: Routledge.

Wiek, A., & Lang, D. J. (2016).Transformational sustainability research methodology.In Sustainability Science (pp. 31-41). Dordrecht: Springer.

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