DATA ANALYSIS
DESCRIPTIVE STATISTICS OF THE STUDY
Simply put descriptive statistics deals with the description of the data in a study as they provide summaries about the sample and measures. The following analyses were arrived at from the data gathered for the purpose of this research using the statistical package for social sciences (SPSS). The first part of the analysis deals with the personal information of the respondents in the study. This includes their gender, age, level of education, branch of the organization, number of years of working with organization, level of experience and level of Computer knowledge.
Frequencies
Statistics
| gender | Age | education | Work experience in Organization | expertise | computer knowledge | department of work | ||
| N | Valid | 351 | 351 | 351 | 351 | 351 | 351 | 351 |
| Missing | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
Frequency Table
Gender
| Frequency | Percent | Valid Percent | Cumulative Percent | ||
| Valid | male | 187 | 53.3 | 53.3 | 53.3 |
| Female | 164 | 46.7 | 46.7 | 100.0 | |
| Total | 351 | 100.0 | 100.0 | ||
SOURCE; FIELD SURVEY 2011
The participants in this survey included 187 males and 164 females with a total percentage for men as 53.3% and for females 46.7. This is an indication that the questionnaire was fairly distributed to both sexes (male and female)
Age
| Frequency | Percent | Valid Percent | Cumulative Percent | ||
| Valid | 18-20 | 5 | 1.4 | 1.4 | 1.4 |
| 21-30 | 94 | 26.8 | 26.8 | 28.2 | |
| 31-40 | 129 | 36.8 | 36.8 | 65.0 | |
| 41+ | 123 | 35.0 | 35.0 | 100.0 | |
| Total | 351 | 100.0 | 100.0 | ||
SOURCE; FIELD SURVEY 2011
From the above table respondents for the survey fell within the following age range 18-20, 21-30, 31-40 and 41 and above (+). There frequencies also include 5, 94, 129, and 123 respectively. The percentages for the various age groups were 1.4, 26.8, 36.8 and 35.0 correspondingly. Most of the participants in the survey within the age range of 31 to 40 and above.
Education
| Frequency | Percent | Valid Percent | Cumulative Percent | ||
| Valid | Diploma | 22 | 6.3 | 6.3 | 6.3 |
| Bachelors | 88 | 25.1 | 25.1 | 31.3 | |
| Masters | 125 | 35.6 | 35.6 | 67.0 | |
| PHD | 59 | 16.8 | 16.8 | 83.8 | |
| others | 57 | 16.2 | 16.2 | 100.0 | |
| Total | 351 | 100.0 | 100.0 | ||
SOURCE; FIELD SURVEY 2011
In response to the question that pondered on respondents’ educational level, 22 indicated diplomas, 88 bachelors degree, 125 masters degree 57 for PHD and 57 for other qualifications. Their percentages also included 6.3, 25.1, 35.6, 16.8, and 16.2 respectively. This shows that a higher number of respondents were asters degree holders as indicated in the table above.
Expertise
| Frequency | Percent | Valid Percent | Cumulative Percent | ||
| Valid | Not Experience | 2 | .6 | .6 | .6 |
| Averagely experienced | 38 | 10.8 | 10.8 | 11.4 | |
| Experienced | 240 | 68.4 | 68.4 | 79.8 | |
| Very Experienced | 71 | 20.2 | 20.2 | 100.0 | |
| Total | 351 | 100.0 | 100.0 | ||
SOURCE; FIELD SURVEY 2011
Commenting on their level of experience on the job 2 employees (who were probably new and learning on the job), 38 indicated to be averagely experienced, 240 were experienced while 71 indicated they were very experienced on their jobs. The percentages for the various level of experience on the job were 0.6, 10.8, 68.4, and 20.2 respectively. Majority of employees were either averagely experienced, experienced or very experienced indicating that only a very minute number was not experienced. This is probably because of the nature of the industry (ICT) which requires a great deal of expertise.
Department of work
| Frequency | Percent | Valid Percent | Cumulative Percent | ||
| Valid | Finance | 48 | 13.7 | 13.7 | 13.7 |
| Marketing | 24 | 6.8 | 6.8 | 20.5 | |
| Hr | 110 | 31.3 | 31.3 | 51.9 | |
| Operations | 108 | 30.8 | 30.8 | 82.6 | |
| Others | 61 | 17.4 | 17.4 | 100.0 | |
| Total | 351 | 100.0 | 100.0 | ||
SOURCE; FIELD SURVEY 2011
Respondents were spread through different departments within their different organizations. 13.7% or respondents indicated they worked at finance departments, 6.8% for marketing, 31.3% for HR, 108% for operations while 17.4 % were from other departments that were not indicated in the items.
Computer Knowledge
| Frequency | Percent | Valid Percent | Cumulative Percent | ||
| Valid | Very poor | 8 | 2.3 | 2.3 | 18.5 |
| Poor | 57 | 16.2 | 16.2 | 16.2 | |
| Neutral | 105 | 29.9 | 29.9 | 48.4 | |
| Good | 111 | 31.6 | 31.6 | 80.1 | |
| Very good | 70 | 19.9 | 19.9 | 100.0 | |
| Total | 351 | 100.0 | 100.0 | ||
SOURCE; FIELD SURVEY 2011
From the above table, 8 respondents indicated that their computer knowledge was very poor, 57 poor, 105 neutral, 111 good while 70 was very good with their percentages being 2.3%, 16.2%, 29.9%, 31.6% and 19.9%. This table shows that a higher number of respondents had at least an average knowledge of computer using the above ratinf standard as stated in the table above.
MEAN FACTOR SCORE FOR WORK EXPERIENCE IN ORGANIZATION
The mean for questions – how long have you been working with this organization and was calculated using the descriptive statistics. This was done to obtain basic information about them. The table below shows the scores for the variable.
| N | Minimum | Maximum | Mean | Std. Deviation | |
| expertise | 351 | 1 | 4 | 2.43 | .917 |
| Valid N (listwise) | 351 |
SOURCE: FIELD SURVEY 2010
From the table above the mean of the number of years of working with experience is 2.43 years with minimum number of years being 1 and the maximum being 4 years. For the question of how long the employee has been working with the organization, the mean of 2.43 means that an employee has been working in this organization for about three years.
.Standard deviation is a measure of how much the data is spread out on both sides of the mean. The wider the disparity between the maximum and minimum values in a distribution, the larger the standard deviation. A standard deviation of 0.917means that on the average, the scores are 0.917 points away from the average for the number of years an employee has worked with organization, it indicates that the values are widely spread.
VALIDITY
According to Kate (2005), it is important to note that high reliability coefficients do not necessarily assume the questionnaires are precisely measuring true activity patterns; they may be alternatively measuring a stable self perception of the subject’s own usual physical activity. That is, the subject is giving consistent, but not necessarily accurate, responses at the two points in time (Baranowski, 1988). Therefore, it is important that the validity (i.e. the degree to which an instrument measures what it is intended to measure) of self-report questionnaires be investigated. There are three forms of validity that can be related to self-report questionnaires: content; construct; and criterion (Morrow, 2002; Sallis & Saelens, 2000).
The validity measurement of this research is the construct validity because the questionnaire was adopted from a researcher and validated by experts. According to Wainer and Braun (1998), the validity in quantitative research is otherwise known as “construct validity”. The construct is the notion or question that establishes which and how data is to be gathered. Construct validity is assessed by comparing trends or relationships from data collected via a self-report questionnaire with established trends or relationships that previous research findings are in clear agreement about (Kate, 2005).
RELIABILITY
According to Joppe (2000), reliability is defined as the extent to which results are reliable over time. It is an exact representation of the total population under study and if the results of that study can be made under the same methodology, then the research instrument is said to be reliable. For the reliability measurement the Cronbach alpha was used. Cronbach‟s alpha reliability coefficient ranges between 0 and 1. The closer it is to 1.0 the greater the internal stability of the items in the scale.
RELIABILITY ANALYSES
Ease of Use
The Cronbach Alpha for the variable Ease was .677 for a total of 5 items tested for the research. Based on the statistics suggested by Sekaran (2000) a cronbach alpha value in the region of 6 to 7 is always considered good in research terminology.
Reliability Statistics
| Cronbach’s Alpha | N of Items |
| .677 | 5 |
Item-Total Statistics
| Scale Mean if Item Deleted | Scale Variance if Item Deleted | Corrected Item-Total Correlation | Cronbach’s Alpha if Item Deleted | |
| It is easy to learn to work with this application | 17.95 | 1.720 | .540 | .576 |
| I think it is easy to make the application do what I want it to | 18.00 | 1.786 | .465 | .611 |
| The application is inflexible | 18.14 | 1.751 | .507 | .592 |
| In general, the application is easy to u | 18.14 | 2.243 | .115 | .754 |
| It is hard to understand how the application works exactly | 17.97 | 1.679 | .572 | .561 |
Item-Total Statistics
Usage
The table below shows the overall alpha for the 4 items measuring perceived usefulness (usage). An alpha co-efficient of 47.2 (Cronbach alpha multiplied by 100) is moderates and signifies a average internal consistency among the selected items since it is approximately 0.5 (50%)
Reliability Statistics
| Cronbach’s Alpha | N of Items |
| .472 | 4 |
Item-Total Statistics
| Scale Mean if Item Deleted | Scale Variance if Item Deleted | Corrected Item-Total Correlation | Cronbach’s Alpha if Item Deleted | |
| The application improves the quality of my work | 13.51 | 1.188 | .155 | .539 |
| The application enables me to do my work quickly | 13.32 | 1.185 | .367 | .318 |
| Using this application improves my personal effectiveness | 13.44 | 1.041 | .473 | .201 |
| I think it is useful to use this application | 13.48 | 1.399 | .148 | .504 |
Support
The table below shows the overall alpha for the 2 items measuring user support. An alpha co-efficient of .526 is moderates and signifies an average internal consistency among the selected items.
Reliability Statistics
| Cronbach’s Alpha | N of Items |
| .526 | 2 |
Item-Total Statistics
| Scale Mean if Item Deleted | Scale Variance if Item Deleted | Corrected Item-Total Correlation | Cronbach’s Alpha if Item Deleted | |
| Whenever I have questions concerning this application I receive support quickly | 4.44 | .276 | .358 | .(a) |
| Questions as to this application are always answered quickly | 4.60 | .241 | .358 | .(a) |
Employee Champion
The Cronbach Alpha for the variable Employee Champion was .724 for a total of 5 items tested for the research. Based on the statistics suggested by Sekaran (2000) a cronbach alpha value in the region of 6 to 7 is always considered good in research terminology.
Reliability Statistics
| Cronbach’s Alpha | N of Items |
| .724 | 5 |
Item-Total Statistics
| Scale Mean if Item Deleted | Scale Variance if Item Deleted | Corrected Item-Total Correlation | Cronbach’s Alpha if Item Deleted | |
| Listen to employees | 17.96 | 1.955 | .535 | .657 |
| Respond to employees | 18.03 | 1.771 | .690 | .590 |
| Satisfy the personal needs of employees | 18.12 | 2.274 | .286 | .750 |
| Take care of employees’ personal needs | 17.99 | 2.357 | .219 | .774 |
| Improve employee commitment | 18.04 | 1.704 | .754 | .561 |
CHANGE AGENT
The table below shows the overall alpha for the 5 items measuring Change agent. A cronbach alpha of .723 is high and shows a strong consistency for all five items Measuring change agent.
Reliability Statistics
| Cronbach’s Alpha | N of Items |
| .723 | 5 |
Item-Total Statistics
| Scale Mean if Item Deleted | Scale Variance if Item Deleted | Corrected Item-Total Correlation | Cronbach’s Alpha if Item Deleted | |
| Helping to adapt to changes | 18.16 | 1.841 | .591 | .632 |
| Initiating change in organizational culture | 18.25 | 1.846 | .551 | .648 |
| Helping the organization cope with future changes | 18.34 | 1.878 | .520 | .660 |
| Renewing the organization | 18.33 | 2.353 | .153 | .797 |
| Encouraging new types of work behavior | 18.13 | 1.794 | .654 | .608 |
ADMINISTRATIVE SUPPORT
The table below shows the overall alpha for the 5 items measuring administrative support. An alpha cronbach of .560 is moderates and signifies an average internal consistency among the selected items.
Reliability Statistics
| Cronbach’s Alpha | N of Items |
| .560 | 5 |
Item-Total Statistics
| Scale Mean if Item Deleted | Scale Variance if Item Deleted | Corrected Item-Total Correlation | Cronbach’s Alpha if Item Deleted | |
| Operational matters | 18.07 | 2.041 | .278 | .532 |
| Offering efficient HR services | 17.98 | 2.105 | .389 | .471 |
| The development of HR processes | 18.17 | 1.615 | .507 | .370 |
| Increasing organizational productivity | 18.14 | 2.440 | .130 | .598 |
| Designing HR processes | 17.95 | 2.148 | .320 | .505 |
Strategic Partner
The overall alpha for the 4 items measuring administrative support is represented in the table below. An alpha cronbach of .344 is moderates and signifies an average internal consistency among the selected items since it is approximately .04.
Reliability Statistics
| Cronbach’s Alpha | N of Items |
| .344 | 4 |
Item-Total Statistics
| Scale Mean if Item Deleted | Scale Variance if Item Deleted | Corrected Item-Total Correlation | Cronbach’s Alpha if Item Deleted | |
| Achieve organizational goals | 13.48 | 1.679 | .165 | .301 |
| Define business strategy | 13.32 | 1.537 | .220 | .242 |
| Implement strategy | 13.44 | 1.584 | .232 | .237 |
| Handle and address strategic issues Make plans | 13.55 | 1.203 | .145 | .367 |
EHRM
The table below shows the overall alpha for the 5 items measuring administrative support. An alpha cronbach of .511 is moderates and signifies an average internal consistency among the selected items.
Reliability Statistics
| Cronbach’s Alpha | N of Items |
| .511 | 5 |
Item-Total Statistics
| Scale Mean if Item Deleted | Scale Variance if Item Deleted | Corrected Item-Total Correlation | Cronbach’s Alpha if Item Deleted | |
| HR should make more use of electronic applications | 17.97 | 1.802 | .293 | .448 |
| HR should not be automated any further | 17.90 | 1.719 | .322 | .427 |
| In general, I’m satisfied with the current level of automation in HR | 18.00 | 1.763 | .475 | .335 |
| E-HRM is an improvement for the organization | 18.07 | 2.332 | .051 | .581 |
| E-HRM is an improvement for the employees | 17.80 | 2.033 | .306 | .444 |
REGRESSION ANALYSIS
LINEAR REGRESSIONS AMONG VARIABLES
- EHRM AND EASE
The model summary table below shows the value of R which is the relationship, the value of R square which predicts the variance and the adjusted R square which states the best value of the R square which can fit into the model. The value of the adjusted R square predicts the variance between the dependent and independent variable; in this case, the value of the adjusted R square implies that 9.3 % of variance is predicted by the variable Ease of use over attitude towards EHRM.
Model summary
| Model | R | R Square | Adjusted R Square | Std. Error of the Estimate | |
| 1 | .305(a) | .093 | .090 | .31266 |
a Predictors: (Constant), EASE
- EHRM AND USAGE
The model summary table below shows the value of the adjusted R square which predicts the variance between the dependent and independent variable; in this case, the value of the adjusted R square implies that 53.9 % of variance is predicted by the variable Usage over attitude towardsEHRM.
Model Summary
| Model | R | R Square | Adjusted R Square | Std. Error of the Estimate |
| 1 | .735(a) | .540 | .539 | .22261 |
a Predictors: (Constant), usage
- EHRM AND SUPPORT
The model summary table below shows the value of the adjusted R square which predicts the variance between the dependent and independent variable; in this case, the value of the adjusted R square implies that 37. 8 % of variance is predicted by the variable user support (support) over attitude towards EHRM.
Model Summary
| Model | R | R Square | Adjusted R Square | Std. Error of the Estimate | |
| 1 | .616(a) | .379 | .378 | .25862 |
a Predictors: (Constant), support
- EHRM AND EMPLOYEE CHAMPION
The model summary table below shows the value of the adjusted R square which predicts the variance between the dependent and independent variable; in this case, the value of the adjusted R square implies that 31. 7 % of variance is predicted by the variable champion (employee champion) over attitude towards EHRM.
Model Summary
| Model | R | R Square | Adjusted R Square | Std. Error of the Estimate | |
| 1 | .565(a) | .319 | .317 | .27095 |
a Predictors: (Constant), champion
- HRM AND CHANGE AGENT
The model summary table below shows the value of the adjusted R square which predicts the variance between the dependent and independent variable; in this case, the value of the adjusted R square implies that 30. 7 % of variance is predicted by the variable change (change agent) over attitude towards EHRM.
Model Summary
| Model | R | R Square | Adjusted R Square | Std. Error of the Estimate | |
| 1 | .556(a) | .309 | .307 | .27293 |
a Predictors: (Constant), change
- EHRM AND ADMINISTRATRATIVE ROLE
The model summary table below shows the value of the adjusted R square which predicts the variance between the dependent and independent variable; in this case, the value of the adjusted R square implies that 72. 7 % of variance is predicted by the variable Administrative over attitude towards EHRM.
Model Summary
| Model | R | R Square | Adjusted R Square | Std. Error of the Estimate |
| 1 | .853(a) | .727 | .726 | .17152 |
a Predictors: (Constant), administration
Model Summary
| Model | R | R Square | Adjusted R Square | Std. Error of the Estimate | Change Statistics | |||||
| R Square Change | F Change | df1 | df2 | Sig. F Change | ||||||
| 1 | .874(a) | .765 | .760 | .16044 | .765 | 186.194 | 6 | 344 | .000 | |
a Predictors: (Constant), administration, EASE, champion, support, usage, change
CORRELATION BETWEEN THE DEPENDENT AND INDEPENDENT
VARIABLES
Simply put Correlation is a statistical measurement of the relationship between two variables such that a variation in one is associated with variation in the other (Babbie 2010). Also certain features of one variable associated with certain features of the other. The variables are not assigned as independent or dependent. Correlation is used in measuring the strength and direction of the existing relationship between the variables. It varies from -1 and 1. The relationship could be either positive or negative with a positive relationship ranging from 0 to 1 and a negative relationship ranging from 0 to -1. The further the value is away from 0, the stronger the relationship. The estimated measure for strength is 0 for no effect, .1 indicates a small effect, .3 indicates a medium effect, and .5 indicates a large effect (Jacob et al. 2002).
The pearson correlation analysis of the table has shown great strength among the variables. All the variables have a relationship of more than 5 % which signifies that the strength of the relationship is ranging from moderate to strong among the variables tested for this research. Employee Championship has the strongest relationship among all the variables which is about 85% which indicate the relationship is very strong.
Correlations
| EHRM | EASE | USAGE | SUPPORT | CHAMPION | CHANGE | ADMINISTRATION | ||
| Pearson Correlation | EHRM | 1.000 | .305 | .735 | .616 | .565 | .556 | .853 |
| Ease | .305 | 1.000 | .250 | .350 | .366 | .313 | .299 | |
| Usage | .735 | .250 | 1.000 | .605 | .518 | .490 | .752 | |
| Support | .616 | .350 | .605 | 1.000 | .506 | .514 | .596 | |
| Champion | .565 | .366 | .518 | .506 | 1.000 | .874 | .530 | |
| Change | .556 | .313 | .490 | .514 | .874 | 1.000 | .563 | |
| Administration | .853 | .299 | .752 | .596 | .530 | .563 | 1.000 | |
| Sig. (1-tailed) | EHRM | . | .000 | .000 | .000 | .000 | .000 | .000 |
| EASE | .000 | . | .000 | .000 | .000 | .000 | .000 | |
| Usage | .000 | .000 | . | .000 | .000 | .000 | .000 | |
| Support | .000 | .000 | .000 | . | .000 | .000 | .000 | |
| Champion | .000 | .000 | .000 | .000 | . | .000 | .000 | |
| Change | .000 | .000 | .000 | .000 | .000 | . | .000 | |
| Administration | .000 | .000 | .000 | .000 | .000 | .000 | . | |
| N | EHRM | 351 | 351 | 351 | 351 | 351 | 351 | 351 |
| Ease | 351 | 351 | 351 | 351 | 351 | 351 | 351 | |
| Usage | 351 | 351 | 351 | 351 | 351 | 351 | 351 | |
| Support | 351 | 351 | 351 | 351 | 351 | 351 | 351 | |
| Champion | 351 | 351 | 351 | 351 | 351 | 351 | 351 | |
| Change | 351 | 351 | 351 | 351 | 351 | 351 | 351 | |
| Administration | 351 | 351 | 351 | 351 | 351 | 351 | 351 | |
- ATTITUDE TOWARDS EHRM AND EASE OF USE
The value of the correlation between Ease of use and attitude towards EHRM is 0.305 and a significance value of 0.00 which is a moderate and significant relationship respectively. H1 Experienced Ease of use is positively related to attitude towards E-HRM systems should therefore be accepted
| Independent/Dependent variable | Correlation | Significance | Relationship |
| Ease of use/ Attitude towards EHRM | 0.305 | 0.000 | Moderate Relationship |
- ATTITUDE TOWARDS EHRM AND PERCEIVED USEFULNESS (USAGE)
A value of 0.735 signifies that there is strong relationship between perceived ease of use and attitude towards EHRM and thus H2: Perceived usefulness is positively related to attitude towards E-HRM systems should be accepted.
| Independent/Dependent variable | Correlation | Significance | Relationship |
| Perceived usefulness / Attitude towards EHRM | 0.735 | 0.000 | Strong Relationship |
- ATTITUDE TOWARDS EHRM AND USER SUPPORT
The value of the correlation between user support and attitude towards EHRM is 0.616 which is a strong relationship. H2 User support is positively related to attitude towards E-HRM systems should therefore be accepted.
| Independent/Dependent variable | Correlation | Significance | Relationship |
| User Support / Attitude towards EHRM | 0.616 | 0.000 | Strong Relationship |
- ATTITUDE TOWARDS EHRM AND EMPLOYEE CHAMPION
The value of the correlation between Employee champion and attitude towards EHRM is 0.565 which is a strong relationship. H4 Preference for the employee champion role is negatively related to Attitude toward EHRM systems should therefore be accepted.
| Independent/Dependent variable | Correlation | Significance | Relationship |
| Employee champion / Attitude towards EHRM | 0.565 | 0.000 | Strong Relationship |
- ATTITUDE TOWARDS EHRM AND CHANGE AGENT
The value of the correlation between Change Agent and attitude towards EHRM is 0.556 which is a strong relationship. H5 Preference for the role of Change agent is positively related attitude towards EHRM systems should therefore be accepted
| Independent/Dependent variable | Correlation | Significance | Relationship |
| Change Agent / Attitude towards EHRM | 0.556 | 0.000 | Strong Relationship |
- ATTITUDE TOWARDS EHRM AND ADMINISTRATIVE EXPERT
A value of 0.853 signifies that there is strong relationship between perceived ease of use and attitude towards EHRM and thus H2: Perceived usefulness is positively related to attitude towards E-HRM systems should be accepted.
| Independent/Dependent variable | Correlation | Significance | Relationship |
| Administrative Expert / Attitude towards EHRM | 0.853 | 0.000 | Strong Relationship |
SUMMARY OF ANALYSIS The Pearson correlation analysis of the table has shown great strength among the variables. All the variables have a relationship of more than 50 % (except for ease which had 0.305) which signifies that the strength of the relationship is ranging from moderate to strong among the variables tested for this research. Administrative support has the strongest relationship among all the variables which is about 85% which indicate a very strong relationship.
