Setup

Load packages

library(ggplot2)
library(dplyr)
## 
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
## 
##     filter, lag
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union
library(statsr)
library(rio)

Install formats

install_formats()
## [1] TRUE

Convert CSV file to Rdata file

convert("COVIDSJData.csv","surveydata.Rdata")

Load data

Make sure your data and R Markdown files are in the same directory. When loaded data file will be called x.

load("surveydata.Rdata")

Part 1: Data

In this project we use the Survey (COVIDSJData.csv) dataset provided by Dr. Giti Javidi from University of South Florida and one of her colleague

The dataset can be downloaded from https://s3.amazonaws.com/nilanjans.net/survey/COVIDSJData.csv

Following is the survey document https://s3.amazonaws.com/nilanjans.net/survey/COVIDSJSurvey.docx

The data extract contains 232 observations of 56 variables.

Random sampling has been used to conduct the survey. The data for the project is generalizable to the entire population of the country. However causal inferences cannot be made from the data as the survey is of observational type.

Part 2: Research questions

1. Do employer-issued COVID-19 messages influence employee perceptions of the firms?

2. Do employer-issued social justice messages influence employee perceptions of the firms?

The dependent variables are:

Columns: V-Z (thoughts after viewing COVID-19 thoughts)

Columns: AJ-AN (thoughts after viewing social justice thoughts)

Columns: AO-AP (trust)

Columns: AQ-AU (loyalty)

Columns: AW and after are demographic variables.

Part 3: Data analysis

Including Plots - Thoughts after viewing COVID-19 message from employer

Below are the plots:

table(x$COVID_After_1)
## 
##  1  2  3  4  5  6  7 
## 28 34 41 17 22 17 15
barplot(table(x$COVID_After_1), main = "More Relaxed --> More Stressed", xlab = "Responses", ylab = "Count", border = "red", col = "blue", density = 10)

table(x$COVID_After_2)
## 
##  1  3  4  5  6  7 
##  3  6 25 36 52 50
barplot(table(x$COVID_After_2), main = "More Worthless --> More Valued", xlab = "Responses", ylab = "Count", border = "red", col = "blue", density = 10)

table(x$COVID_After_3)
## 
##  1  2  3  4  5  6  7 
##  2  1  4 18 38 55 52
barplot(table(x$COVID_After_3), main = "More Disrespected --> More Respected", xlab = "Responses", ylab = "Count", border = "red", col = "blue", density = 10)

table(x$COVID_After_4)
## 
##  1  3  4  5  6  7 
##  3  3 27 35 58 44
barplot(table(x$COVID_After_4), main = "More Unimportant --> More Important", xlab = "Responses", ylab = "Count", border = "red", col = "blue", density = 10)

table(x$COVID_After_5)
## 
##  1  2  3  4  5  6  7 
##  1  3  8 22 33 45 57
barplot(table(x$COVID_After_5), main = "More Unsafe --> More Safe", xlab = "Responses", ylab = "Count", border = "red", col = "blue", density = 10)

Including Plots - Thoughts after viewing social justice message from employer

Below are the plots:

table(x$SJ_After_1)
## 
##  1  2  3  4  5  6  7 
## 27 26 22 30 21 21 21
barplot(table(x$SJ_After_1), main = "More Relaxed --> More Stressed", xlab = "Responses", ylab = "Count", border = "red", col = "blue", density = 10)

table(x$COVID_After_2)
## 
##  1  3  4  5  6  7 
##  3  6 25 36 52 50
barplot(table(x$SJ_After_2), main = "More Worthless --> More Valued", xlab = "Responses", ylab = "Count", border = "red", col = "blue", density = 10)

table(x$COVID_After_3)
## 
##  1  2  3  4  5  6  7 
##  2  1  4 18 38 55 52
barplot(table(x$SJ_After_3), main = "More Disrespected --> More Respected", xlab = "Responses", ylab = "Count", border = "red", col = "blue", density = 10)

table(x$COVID_After_4)
## 
##  1  3  4  5  6  7 
##  3  3 27 35 58 44
barplot(table(x$SJ_After_4), main = "More Unimportant --> More Important", xlab = "Responses", ylab = "Count", border = "red", col = "blue", density = 10)

table(x$COVID_After_5)
## 
##  1  2  3  4  5  6  7 
##  1  3  8 22 33 45 57
barplot(table(x$SJ_After_5), main = "More Unsafe --> More Safe", xlab = "Responses", ylab = "Count", border = "red", col = "blue", density = 10)

Trust: Do you agree that XYZ management will make decisions that are also good for you?

Below is the plot:

table(x$Trust)
## 
##  1  2  3  4  5  6  7 
##  3  5  4 12 39 62 49
barplot(table(x$Trust), main = "Strongly Disagree --> Strongly Agree", xlab = "Responses", ylab = "Count", border = "red", col = "blue", density = 10)

Trust2: Do you agree that XYZ management can be trusted to treat you fairly?

Below is the plot:

table(x$Trust2)
## 
##  1  2  3  4  5  6  7 
##  2  4  4 12 35 56 61
barplot(table(x$Trust2), main = "Strongly Disagree --> Strongly Agree", xlab = "Responses", ylab = "Count", border = "red", col = "blue", density = 10)

Loyalty Based on the two messages you just viewed, please indicate how much you agree or disagree with the following statements

Below are the plots:

I am wiling to put in a great deal of effort to help this organization succeed

table(x$Loyalty_1)
## 
##  1  2  3  4  5  6  7 
##  1  2  3 13 26 73 56
barplot(table(x$Loyalty_1), main = "Strongly Disagree --> Strongly Agree", xlab = "Responses", ylab = "Count", border = "red", col = "blue", density = 10)

This is a good place to work

table(x$Loyalty_2)
## 
##  1  2  3  4  5  6  7 
##  3  2  2 12 22 65 67
barplot(table(x$Loyalty_2), main = "Strongly Disagree --> Strongly Agree", xlab = "Responses", ylab = "Count", border = "red", col = "blue", density = 10)

My values are similar to the organization’s values

table(x$Loyalty_3)
## 
##  1  2  3  4  5  6  7 
##  5  1  6  9 19 71 63
barplot(table(x$Loyalty_3), main = "Strongly Disagree --> Strongly Agree", xlab = "Responses", ylab = "Count", border = "red", col = "blue", density = 10)

This organization inspires the best job performance from me

table(x$Loyalty_4)
## 
##  1  2  3  4  5  6  7 
##  4  1  5 13 33 63 54
barplot(table(x$Loyalty_4), main = "Strongly Disagree --> Strongly Agree", xlab = "Responses", ylab = "Count", border = "red", col = "blue", density = 10)

I care about the fate of this organization

table(x$Loyalty_5)
## 
##  1  2  3  4  5  6  7 
##  4  3  6 14 26 60 60
barplot(table(x$Loyalty_5), main = "Strongly Disagree --> Strongly Agree", xlab = "Responses", ylab = "Count", border = "red", col = "blue", density = 10)

Findings

Based on the graphical results we can say that the overall employees are satisfied with employers from the messages sent by the firms.

Conclusion

Based on the demographic variables (like position, age, gender, household income, etc) we can do further detailed analysis.