Put it all together

Running head: JOB ATTITUDES ASSESSMENT 1

JOB ATTITUDES ASSESSMENT 10

Analysis of Employees’ Job attitudes Michael A. Leonard Walden University IPSY 8579 Job Attitudes, Measurement, and Change Professor Deborah Peck

1. Introduction

The purpose of a job attitude assessment is to help determine employees’ perception, availability, and feelings towards an organization or a company (Bashaw & Grant, 2014). Reliability is employed to show the degree to which a test score or data is consistent across applications or time. There are four types of reliability that are often employed when assessing employees’ job attitude: the test-retest reliability, equivalence reliability, internal reliability, and inter-rater reliability. To this end, this paper will compute different components of the job attitude assessment that were used. It begins by showing a computation of coefficient alpha estimates of reliability, then frequency responses for each of the items that were used to evaluate employees’ job attitude, overall scores for the separate instruments that were selected, and finally computes Pearson’s product moment correlations for all variables. Comment by Deb: This isn’t necessary but okay for this assignment. Your goal is to write this as though you are the consultant to Walden Sports so you are considered the ‘expert’ and doing data collection, analysis and then recommendations. If the final paper were about reliability or stats in general, then something like this would be good to include. Comment by Deb: This is good. You are missing the antecedent variables though – that is half of the assignment and analysis.

2. Computation of Coefficient Alpha Estimates of Reliability Comment by Deb: The instructions for this assignment are to create an APA formatted Table 1 with a lot of the stats included and a separate Table 2 for the frequencies of all the variables for job attitudes. So, although you might have the right values, you don’t have them formatted into a table correctly and you do not have an APA formatted tables. You can include this SPSS output and the syntax and the appendix for the final paper. See the announcements in the classroom for examples. There are also resources in the writing center about formatting tables from SPSS to APA.

The following results were obtained from the SPSS analysis about the coefficient alpha estimates of reliability.

Table 1: Global Job Satisfaction
Cronbach's Alpha	Cronbach's Alpha Based on Standardized Items	No. of Items
.951	.951	3

Table 2: Organizational Commitment (Affective Commitment)
Cronbach's Alpha	Cronbach's Alpha Based on Standardized Items	No. of Items
.956	.957	6

Table 3: Organizational Commitment (Normative Commitment)
Cronbach's Alpha	Cronbach's Alpha Based on Standardized Items	No. of Items
.931	.932	6

Table 4: Organizational Commitment (Continuance Commitment)
Cronbach's Alpha	Cronbach's Alpha Based on Standardized Items	No. of Items
.933	.933	6

Table 5: Organizational Commitment (All Three Scales)
Cronbach's Alpha	Cronbach's Alpha Based on Standardized Items	No. of Items
.946	.947	18

Table 6: Job Involvement
Cronbach's Alpha	Cronbach's Alpha Based on Standardized Items	No. of Items
.944	.955	6

Table 1 shows that the coefficient alpha for the global job satisfaction variable is statistically significant since the computation yields a Cronbach’s alpha of .951 when n = 3. For this reason, the global job satisfaction is significantly reliable (Bashaw & Grant, 2014). The implication of this is that there is a direct relationship between employees’ job satisfaction and job attitude. Table 2 also reveals that the variable affective commitment, which is a component of organizational commitment, is statistically significant. Its Cronbach’s alpha when n = 6 is .957. As such, there exists a significant degree of reliability of employees’ job satisfaction to affective commitment (Darwish, 2000). It can be therefore be deduced that there is an association employees’ affective commitment and their job attitudes. Comment by Deb: This doesn’t make any sense. Why does the value of .951 indicate anything about significance? Reliability can be determined without significance and they are separate functions. Comment by Deb: Direct relationship is a bit broad and implies a correlation. We are evaluating reliability here so explain what you mean by a direct relationship in regard to reliability and the Alpha values. We have to use technical stats terms in this section. So look up reliability and it is more about acceptable values in an approved range. You need to find some literature that gives you a range to know where the cut-offs will be. These comments are the same for the rest of your narrative analysis below for this stats procedures. Comment by Deb: Now you are focused on reliability – this is closer but you can’t say it is significant unless you show that test and that is separate from the alpha value.

Similarly, the coefficient alpha that is corresponding to the normative commitment, which is a component of organizational commitment, is statistically significant. It also exhibits a considerable degree of reliability as its Cronbach’s alpha is .932 when n=6 (Dobrea & Găman, 2011). This proves that there exists a relationship between, job attitude and employees’ normative commitment. Additionally, there exists a relationship between continuance commitment of employees and job attitude as can be shown in table 4 where the coefficient alpha is statistically significant alongside a considerable degree of reliability since its Cronbach’s alpha is .933 (Darwish, 2000). Furthermore, there is a statistical significance and reliability between organizational commitment and employees’ job attitudes (Cronbach’s alpha =.946 when n=18) and there same is with job involvement (Cronbach’s alpha =.944 when n=6). Comment by Deb: Don’t use the word ‘prove’ – as that is only close to being used in actual experiments and there is always ‘room for error’ in science – so we aren’t proving anything. We are indicating results…. You will need to distinguish between relationship and reliability – although there can be correlations among them, that is determined from a Pearson correlation analysis, not the alpha analysis.

3. Computation of an Overall Score for the Separate Instruments Selected

The following table is a pull up of an SPSS output regarding the different instruments that were selected to help gauge employees’ job satisfaction.

Table 7: Case Summary
	Cases
	Valid	Missing	Total
	N	Percent	N	Percent	N	Percent
Global Job Satisfaction	21	13.5%	134 Comment by Deb: I am not sure where you are getting your data but there are no missing cases in any of the items from the dataset provided for this exercise. I am not sure what the purpose of this case summary provides to the discussion and assignment requirements.	86.5%	155	100.0%
Organizational Commitment	74	47.7%	81	52.3%	155	100.0%
Job Involvement	54	34.8%	101	65.2%	155	100.0%

From the table, different values were obtained for the selected elements’ standard deviation. For the variable job satisfaction, the results exhibited consistency with outcomes that were obtained for the three items that were chosen. The mean, mM, was found to be 1.62 while the standard deviation, SDS, was found to be 3.59. The variable organizational commitment also had results that were consistent for all the items that sub-variables that were considered. For this variable, m M = 1.737 while SD = 3.37. Another variable that also showed consistency in its sub-variables was the job involvement variable, which registered a mean of 1.162 and SD as 3.42. Comment by Deb: What table? Refer to it by number. But see previous comments about having only two tables and APA formatted. Comment by Deb: I don’t see a table that shows SD. Comment by Deb: Where is the table for this? Comment by Deb: These numbers might be transposed?

4. Computation of the Frequency of Responses for Each Item

The table below is an SPSS output for the computation of frequencies of responses for each of the items that were used to assess employees’ job attitude.

Table 8: Global Job Satisfaction Frequencies
	Responses	Percent of Cases
	N	Percent
Global Job Satisfaction	JS1: All in all, I am satisfied with my job. Comment by Deb: These might be the right results but refer to the examples in the classroom to see how to format this data into one table for all variables. You need to include all of the scale anchor values not just one response.	15	32.6%	71.4%
	JS2: In general, I like my job.	14	30.4%	66.7%
	JS3: In general, I like working at this company	17	37.0%	81.0%
Total	46	100.0%	219.0%
a. Dichotomy group tabulated at value 1.
Table 9: Organizational Commitment Frequencies
	Responses	Percent of Cases
	N	Percent
Organizational Commitment	AC6: I really feel as if this organization's problems are my own.	24	6.9%	32.4%
	NC1: I feel an obligation to remain with this company.	35	10.1%	47.3%
	NC2: I would feel guilty if I left this company now.	37	10.6%	50.0%
	NC3: The company deserves my loyalty.	23	6.6%	31.1%
	NC4: I would not leave this company right now because I have a sense of obligation to the people in it.	26	7.5%	35.1%
	NC5: Even if it were to my advantage, I do not feel it would be right to leave my organization now.	34	9.8%	45.9%
	NC6: I owe a great deal to this organization.	30	8.6%	40.5%
	CC1: It would be very hard for me to leave this company right now, even if I wanted to.	13	3.7%	17.6%
	CC2: Too much of my life would be disrupted if I decided I wanted to leave this company right now.	24	6.9%	32.4%
	CC3: Right now, staying with this company is a matter of necessity as much as desire.	22	6.3%	29.7%
	CC4: I feel that I have too few options to consider leaving this company.	28	8.0%	37.8%
	CC5: One of the few negative consequences of leaving this organization would be the scarcity of available alternatives.	24	6.9%	32.4%
	CC6: If I had not already put so much of myself into this organization, I might consider working elsewhere.	28	8.0%	37.8%
Total	348	100.0%	470.3%
a. Dichotomy group tabulated at value 1.
Table 10: Job Involvement Frequencies
	Responses	Percent of Cases
	N	Percent
Job Involvement	JI1: The major satisfaction in my life comes from my job.	34	21.0%	63.0%
	JI2: The most important things that happen to me involve my work.	30	18.5%	55.6%
	JI3: I'm really a perfectionist about my work.	21	13.0%	38.9%
	JI4: I live, eat, and breathe my job	25	15.4%	46.3%
	JI5: I am very much involved personally with my work.	21	13.0%	38.9%
	JI6: Most things in life are not more important than work.	31	19.1%	57.4%
Total	162	100.0%	300.0%
a. Dichotomy group tabulated at value 1.

The frequency assessment was employed to help in establishing the percentages as well as number of participants who selected each of the scale anchors for the different items that were under investigation (Dobrea & Găman, 2011). For instance, the number of people who answered (1[Strongly Disagree] or 7[Strongly Agree] on Job Satisfaction JS01?) similarly, the frequency of responses was used to help acquire detailed information concerning how workers actually respond to analytical questions as well as the job attitude evaluation (Dobrea & Găman, 2011). Comment by Deb: This is okay but the first part of this sentence is confusing.

5. Computation of Pearson’s Product Moment Correlations for all variables

To compute Pearson’s product moment correlation for all the variables that were under consideration, SPSS was used to provide a summary of frequency scrutiny of the three selected variables, as shown the tables of frequencies above.

From the frequency evaluation graph, it is clear that there exists a number of correlations regarding the variable global job satisfaction. Nonetheless, the most crucial positive correlation is noted between the variable JS03 and JS01, whose r = .88 when n = 6, and Pearson’s product moment (p) = .000. Similarly, there exist several correlations regarding organizational commitment. Nevertheless, the most essential of the correlations is noted between AC05 and AC03, whose r = .887 when n = 18, and p = .000. Last but not least, regarding the variable job involvement, there is are noted several correlations. However, the most important of them is that between JL01 and JL03, whose r = .781 when n = 18 and p = .0000. Comment by Deb: You can’t determine correlation from a frequency table. You don’t have the correlation table shown so I can’t say if these numbers are accurate. Comment by Deb: This interpretation doesn’t make any sense. Why is this the most crucial positive correlation? You didn’t explain the values correctly. Comment by Deb: Now you say the most essential correlation is between these variables. How does that differ from the crucial correlation above? Comment by Deb: Now we have the most important – so I am confused on how you are interpreting these to apply to your recommendations.

References Comment by Deb: It is good you brought in some literature to support some of the comments you made but I think you might be confusing some of the terminology and how the stats are used/interpreted. It might be good for you to find some SPSS and stats literature/sources as well to help you understand.

Bashaw, E. R. & Grant, S. E. (2014). Exploring the distinctive nature of work commitments: Their relationships with personal characteristics, job performance, and propensity to leave. Journal of Personal Selling and Sales Management, 14(9), 41-56.

Darwish, Y. (2000). Organizational Commitment and Job Satisfaction as Predictors of Attitudes toward Organizational Change in a Non-Western Setting. Personnel Review, 29(4), 6–25.

Dobrea, R. & Găman, A. (2011). Aspects of the Correlation between Corporate Social Responsibility and Competitiveness of Organization, Revisit. Economic, Serial Management, 14(1), 236 - 298.