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Qualitative Research Results Technologies Report


Introduction

Research studies are important in academic pursuit as they allow students to broaden their knowledge of various disciplines (Gorard, 2013). However, it is important for students to understand various research methods available, and identify which method is best applicable. Research analysis may be qualitative or quantitative in nature.

The choice of the research analysis is influenced by several factors. However, students may access different technologies available to facilitate their research study. This paper reviews different technologies available to improve qualitative research results. The paper also highlights the difference between inductive and deductive reasoning in result interpretation. Finally, the research investigates the relationship between communication, remuneration and job satisfaction.

Literature Review

Employee satisfaction is important for organizational development. This has influenced researchers’ decision to investigate the factors that influence employee satisfaction. Two important factors that may influence employee satisfaction are remuneration and communication (May, & Mumby, 2005).

In their study, May & Mumby (2005) investigate the influence of staff salary on employees’ satisfaction levels. A job satisfaction survey is used to test how employees are comfortable with their jobs. The result of the research shows that employees that are paid more, tend to be more satisfied than their counterparts who receive less payment (May, & Mumby, 2005).

Another research study investigates the influence of smooth interpersonal communication and staff performance. During the research, participants were asked to rate their communication with the superiors. These same participants were then required to respond to a job satisfaction survey. The outcome of the report indicated a positive relationship between organizational communication and employee satisfaction (McPhee & Zaug, 2000).

Initial studies indicate the relationship between employee satisfaction, and communication or employee satisfaction and remuneration. However, this study investigates the relationship between job satisfaction and the two variables (remuneration and organizational communication).

Dependent and Independent Variables

The study investigates two independent variables and one dependent variable. The independent variables include remuneration and communication in the organization, while the dependent variable is job satisfaction.

Hypothesis

  1. There is a positive relationship between job satisfaction and remuneration?
  2. There is a positive relationship between job satisfaction and interpersonal communication?

Qualitative Research Technologies

The importance of research studies has influenced the development of statistical software dedicated to qualitative analysis. A statistical application used for qualitative analysis is SAS software.

It is a complete package capable of performing data-management functions during research studies. SAS has a complete collection of statistical data and application. However, SAS software is complex and difficult to understand. Although some functions can be accessed from the pull-down tab, the SAS software is based on codes (Der & Everittt, 2009).

IBM SPSS software is commonly used in qualitative research analysis. Its functions are similar to the SAS software, however, SPSS is used globally (Acock, 2005). SPSS software can be used for text analysis. The SPSS Text Analysis for Surveys can be used for qualitative analysis data derived through surveys, for instance, answers to open-ended questions. STATA software is another research tool. However, many users consider STATA more complex than SAS and SPSS (Acock, 2005).

Another technology for qualitative analysis is NVivo (Dearne, 2008). This software is used for content analysis and qualitative studies. NVivo is characterised by exceptional visuals and is ideal for text based data analysis.

Deductive and inductive Reasoning

Notwithstanding the qualitative research technology a researcher chooses to use, results will be generated. One other important activity a researcher must be conversant with is the ability to interpret the results generated from applying the qualitative technology. Two common approaches to reasoning are deductive and inductive reasoning.

Also called deduction, deductive reasoning is a simple type of valid thinking. It begins with a hypothesis or general statement, and then investigates the potential of reaching a particular, rational decision. In science, theories are tested via deduction.

Deductive reasoning considers whatever is true for a group of things generally, to be true for every member of the said group (Sternberg, 2009). For example, “All babies cry. Patrick is a baby. Therefore, Patrick cries.” The soundness of deductive reasoning depends on how correct the hypothesis is.

It is considered that the theory “All babies cry” and “Patrick is a baby” are correct. Thus, the decision is rational and correct. It may be possible to draw conclusions even when the generalisation is incorrect. An incorrect generalisation may lead to a correct or incorrect conclusion. For example, the premise, “All babies drool. Patrick is a baby. Therefore, Patrick drools,” is valid rationally, but incorrect since the first statement is not true.

Also referred to as induction, inductive reasoning is the reverse of deduction (Copi, Cohen, & Flage, 2007). In induction, wide generalisations are made from detailed evidence. Although every premise made may be correct, inductive reasoning considers the possibility of a wrong conclusion. For example, “Patrick is a baby. Patrick drools. Therefore, all babies drool.” The decision is not a logical reflection of the statements.

Both deduction and induction are important in scientific research. Researchers use inductive reasoning to develop theories and hypotheses (Baronett, 2008), and then use deduction to use the developed theories in specific circumstances (Holyoak & Morrison, 2005).

Research Study

This research investigates how superior-subordinate communication and remuneration influences job satisfaction. The questionnaire below was distributed to 50 participants. The questionnaire comprised of eight questions testing participant’s job satisfaction.

Questionnaire

Gender

  • Male
  • Female

Age Group

  • 18-24
  • 25-29
  • 30-34
  • 35-39
  • 40-44
  • 45-49
  • 50-Above

Annual Remuneration

  • < $20000
  • $20,000 to $50,000
  • $51,000 to $100,000
  • $101,000 to $150,000
  • $151,000 to $200,000
  • $201,000 to $300,000
  • $301,000 to $400,000
  • >$400,000

How satisfied are you with the communication between you and your superior?

  • Very Unsatisfied,
  • Unsatisfied,
  • Moderately Satisfied,
  • Satisfied ,
  • Very Satisfied

Are you satisfied with your job?

  • Very Unsatisfied,
  • Unsatisfied,
  • Moderately Satisfied,
  • Satisfied,
  • Very Satisfied

How well are you paid for the job you do?

  • Very Lowly Paid,
  • Lowly Paid
  • Moderately Paid
  • Well Paid
  • Very Well Paid

How practical are your boss’ expectations?

  • Very Impractical
  • Impractical
  • Moderately Practical
  • Practical
  • Very Practical

Do you like your employer?

  • No
  • Indifferent
  • Yes

Would you like to continue working for this company?

  • No
  • Indifferent
  • Yes

Analysis of Results

The three tables predict the relationship between communication and employee satisfaction based on SPSS analysis.

Model Summary
Model R R Square Adjusted R Square Std. Error of the Estimate
1 .641a .411 .398 .799
a. Predictors: (Constant), How satisfied are you with the communication between you and your superior?
ANOVAa
Model Sum of Squares df Mean Square F Sig.
1 Regression 21.356 1 21.356 33.430 .000b
Residual 30.664 48 .639
Total 52.020 49
a. Dependent Variable: Are you satisfied with your job?
b. Predictors: (Constant), How satisfied are you with the communication between you and your superior?
Coefficientsa
Model Unstandardized Coefficients Standardized Coefficients t Sig.
B Std. Error Beta
1 (Constant) 1.581 .457 3.459 .001
How satisfied are you with the communication between you and your superior? .677 .117 .641 5.782 .000
a. Dependent Variable: Are you satisfied with your job?

The next three tables predict the relationship between communication and employee satisfaction based on SPSS analysis

Variables Entered/Removeda
Model Variables Entered Variables Removed Method
1 How well are you paid for the job you do?b . Enter
a. Dependent Variable: Are you satisfied with your job?
b. All requested variables entered.
Model Summary
Model R R Square Adjusted R Square Std. Error of the Estimate
1 .671a .450 .438 .772
a. Predictors: (Constant), How well are you paid for the job you do?
ANOVAa
Model Sum of Squares df Mean Square F Sig.
1 Regression 23.389 1 23.389 39.212 .000b
Residual 28.631 48 .596
Total 52.020 49
a. Dependent Variable: Are you satisfied with your job?
b. Predictors: (Constant), How well are you paid for the job you do?
Coefficientsa
Model Unstandardized Coefficients Standardized Coefficients t Sig.
B Std. Error Beta
1 (Constant) 1.518 .433 3.508 .001
How well are you paid for the job you do? .652 .104 .671 6.262 .000
a. Dependent Variable: Are you satisfied with your job?

References

Acock, A. C. (2005). SAS, Stata, SPSS: A Comparison. Journal of Marriage and Family, 67 (4), 1093–1095

Baronett, S. (2008). Logic. NJ: Pearson Prentice Hall.

Copi, I. M., Cohen, C., & Flage, D. E. (2007). Essentials of logic. Upper Saddle, NJ: Pearson Education, Inc.

Dearne, K. (2008). Not easy being green, but audits help. Australian IT. Web.

Der, G. & Everittt, B. S. (2009). Basic Statistics using SAS Enterprise Guide. Journal of the Royal Statistical Society: Series A, 172 (2), 530.

Gorard, S. (2013). Research Design: Robust approaches for the social sciences, London: SAGE

Holyoak, K. & Morrison, R. (2005). The Cambridge Handbook of Thinking and Reasoning. New York: Cambridge University Press

May, S. Mumby, D. K. (2005). Engaging Organizational Communication Theory and Research. Thousand Oaks, CA: Sage.

McPhee, R. & Zaug, P. (2000). The Communicative Constitution of Organizations: A framework for explanation. Electronic Journal of Communication, 10 (1-2), 1–16.

Sternberg, R. J. (2009). Cognitive Psychology. Belmont, CA: Wadsworth.

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IvyPanda. (2020, April 9). Qualitative Research Results Technologies. Retrieved from https://ivypanda.com/essays/qualitative-research-results-technologies/

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"Qualitative Research Results Technologies." IvyPanda, 9 Apr. 2020, ivypanda.com/essays/qualitative-research-results-technologies/.

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IvyPanda. "Qualitative Research Results Technologies." April 9, 2020. https://ivypanda.com/essays/qualitative-research-results-technologies/.

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IvyPanda. 2020. "Qualitative Research Results Technologies." April 9, 2020. https://ivypanda.com/essays/qualitative-research-results-technologies/.

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IvyPanda. (2020) 'Qualitative Research Results Technologies'. 9 April.

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