MGMT3540 Assignment #10—Regression
XYZ Inc. has just collected survey data from their current employees. You are asked to analyze and interpret the data so that you can help the CEO make evidence-based decisions to improve employee engagement. The CEO of the company has asked the VP HR to analyze the data and would like to understand the drivers of employee engagement as well as factors affecting employees’ intention to quit.
The VP of HR has asked you (the HR Analytics Manager) to analyze and report about a few questions.
Question 1
Instructions: Below is a correlation table summarizing the results of the study that looked at seven variables:
All the variables in this study were measured on a scale of 1 to 5 ranging from “Strongly Disagree” to “Strongly Agree” with higher scores reflecting higher degrees of agreement and/or higher levels of the variable.
Information about the variables (see also Assignment #8 for detailed descriptions of the items):
Manager Motivating Behaviors = Employees’ perceptions of the degree to which their managers motivate and encourage them.
Autonomy = The extent to which employees have the freedom and flexibility to choose how they complete their work.
Justice = The degree to which employees perceive fairness in the process of how their organizations resolve disputes and allocate resources.
Job Satisfaction = How satisfied employees are with their current job.
Intention to Quit = The extent to which employees intend to leave the job/organization.
Variable Name | M | SD | 1 | 2 | 3 | 4 | 5 | 6 | 7 |
1. Manager Motivating Behaviors | 3.75 | 0.99 | – | ||||||
2. Autonomy | 3.88 | 0.85 | .307** | – | |||||
3. Justice | 2.76 | 0.77 | .338** | .264** | – | ||||
4. Job Satisfaction | 3.82 | 0.84 | .382** | .405** | .325** | – | |||
5. Intentions to Quit | 2.33 | 1.02 | -.210** | -.209** | -.248** | -.369** | – | ||
6. Engagement | 3.51 | 0.83 | .105** | .210** | .190** | .299** | -.508** | – | |
7. Perceived Organizational Support | 2.79 | 0.70 | .323** | .227** | .411** | .321** | -.356** | .269** | – |
Engagement = The extent to which employees are fully absorbed by and enthusiastic about their work.
Perceived Organizational Support = The degree to which employees believe that their organization cares about them and provides adequate support.
Correlations with a single ‘*’ are significant at p < 0.05 and those with ‘**’ are significant at p < 0.01
- Using information from the correlation matrix above, answer the following questions:
- What are the variables that are significantly correlated with engagement? In other words, what could potentially drive employee engagement?
For each variable that is significantly correlated with engagement, please explain the nature of the relationship (i.e., are they positively or negatively correlated and what that means).
1.Based on the correlations above, list the three strongest drivers of engagement. Based on your experiences at work and your readings in this course and outside, come up with the “Logic” for why these factors either positively or negative related to employee engagement (e.g., why would perceptions of organization support be positively related to employee engagement?)
HINT 1: Establish a logic/story/theory for the relationship between two variables.
HINT 2: It would be helpful to revisit some theories you’ve learned in your Organizational Behavior or Introduction to HR course. It is also a GREAT idea to search for press articles and scholarly articles to see what arguments others have made before. Cite the source using either APA or MLA style.
HINT 3: The sign (positive or negative) of the correlation does not dictate the strength of the relationship. In other words, a positive relationship may not always be stronger than a negative relationship. The absolute value of the coefficient determines the magnitude of the influence of predictors (X) on outcomes (Y).
Question 2
The VP of HR now wants to know where the organization should focus its attention by identifying the most important driver of employee engagement. As the resident HR Analytics expert, you run a regression analysis to examine this question.
Instructions: Below is a table summarizing the results of the regression analysis that looked at the potential drivers of employee engagement.
Model Coefficients (Dependent Variable) – Engagement | |||||||||||
Predictor | Estimate | SE | t | p | Stand. Estimate | ||||||
Intercept | 1.2880 | 0.1395 | 9.233 | < .001 | |||||||
Manager Motivating Behavior | -0.0109 | 0.0309 | -0.352 | 0.725 | -0.0132 | ||||||
Autonomy at Work | 0.1459 | 0.0354 | 4.116 | < .001 | 0.1503 | ||||||
Perceived Organizational Support | 0.2811 | 0.0432 | 6.514 | < .001 | 0.2393 | ||||||
- Using information from the regression table above, answer the following questions:
- What can you infer from the results of the regression analysis? In other words, what factors significantly influence engagement?
Which factor is the strongest driver of employee engagement? Is it a positive or negative relationship and what does this mean? Explain how you made this determination as well as how this variable relates to engagement.
How do the estimates from the regression table differ from statistics from the correlation table? How do you interpret the differences
Question 3
Finally, you are asked to investigate factors that could influence employees’ intention of quitting the company. Once again, you run a regression analysis to identify the drivers of intentions to quit. The results of this analysis are provided below.
Model Coefficients (Dependent Variable) – Intention to Quit | |||||||||||
Predictor | Estimate | SE | t | p | Stand. Estimate | ||||||
Intercept | 5.934 | 0.1482 | 40.04 | < .001 | |||||||
Engagement | -0.513 | 0.0382 | -13.44 | < .001 | -0.423 | ||||||
Justice | -0.132 | 0.0415 | -3.18 | 0.002 | -0.101 | ||||||
Job Satisfaction | -0.254 | 0.0399 | -6.37 | < .001 | -0.208 | ||||||
- Using the information from the regression analysis above, answer the following questions:
- What can you infer from the results of the regression analysis? In other words, what factors significantly influence intentions to quit the company?
4.Provide the ‘Logic’ underlying the relationships between each driver and employee intentions to quit. In other words, why do you think employees are likely to quit when they experience low levels of job satisfaction, justice perceptions, and engagement?
Which factor is the strongest driver of intentions to quit? Explain how you made this determination as well as how this variable relates to intentions to quit (is it a positive or negative relationship and what does this mean?).
Question 4
- Given the findings from these 3 analyses above, what would you report back to the VP HR about where the organization should focus on if they want to improve employee engagement and reduce turnover?
(HINT: discuss how organizations should prioritize their resources to solve these issues based on your findings/analyses in the previous 3 questions. Also, are there any ways to “kill two birds with one stone”— solving both engagement and turnover issues together with one mov
Question 5
- Your VP HR is asking for your help to discover drivers of job satisfaction using another regression analysis.
- In this analysis, pick three variables that you think would have strong impacts on job satisfaction. For each variable, explain the logic for why and how they can influence job satisfaction in at least 2-3 sentences.
Variable 1 is:
Logic:
Variable 2 is:
Logic:
Variable 3 is:
Logic:
- Paste the regression table (results) from Jamovi below.
Does your analysis confirm your “logic”? Or does it say otherwise? (HINT: Even if the results do not support your logic, that’s still a meaningful finding—at least you’ve ruled out those factors as drivers of job satisfaction and they you know that focusing on them would not be useful. Grading of this question will NOT be based on whether your logic was supported or not; rather, it’s based on whether you’ve correctly interpreted the regression results).