Statistical analysis of results.

Statistical analysis of results.

Descriptive statistics.

The data set on employees was analyzes using SPSS to answer help answer the research questions. Descriptive statistics provide a feel of the data i.e. finding missing values and outliers in the data.

Table 1: Description of the data

Table 1 above gives a feel of the data. The data contains no missing variables.

The table below shows descriptive statistics for factors affecting sustainability and a scale of their importance.

Table 2 weighing the importance of factors

From the table above, a majority of the employees agree that human resource management practices are the most important practices in the determination of the extent of creativeness and innovation among the employees. Creativeness is the largest contributor to sustainability according to the employees.

RQ 1: How does employee creativity influence the sustainability of MNs in the host country?

In this question, this report aims to examine whether the creativity of an employee has any on MNCs’ sustainability in the host country.

H₀: There exists a relationship between employees’ creativity and the sustainability of MNC.

H₁: There exists no relationship between employees’ creativity and the sustainability of MNC.

Decisions for the hypotheses in this question will be made through the use of summary descriptive statistics. The variable under analysis is the competitiveness variable defined form the average of the responses from Q12.

It is important to investigate the views on creativity about gender to determine whether any differences exist. The table below shows the results of the independent samples t-test.

Table 3: Differences in creativity based on gender.

From table 3 above, the test statistic of the test is 0.446 which as a p-value of 0.622 which is greater than 0.05 which is the alpha-level of significance. There exist no significant differences in the views about creativity based on gender.

Table 4 below shows the ANOVA test for differences in views on creativity between various age groups.

Table 4: ANOVA test for creativity based on age group

From table 4 above, the f-value of the test for significance of the difference between the means of the age groups is 3.457 and has a significant level of 0.11 which is above the 0.05 significance level. This implies that there exists no difference between the views on creativity between all the age groups.

The table below shows the regression output for the relationship between age and views on the impact of creativity on sustainability.

Table 5 Regression model between age and creativity

From table 5 above, the relationship between the two variables can be represented by the equation y=-0.094x+3.723 where y is the employees’ view on creativity while x is the age group of the employee. The significance of the test is 0.351 which is above the 0.05 alpha level of significance implying that age is significant when collecting views on the impact of creativity on sustainability.

RQ 2: How does employee innovativeness influence the sustainability of MNC in the host country?

H₀: There exists a relationship between employee innovativeness’ and MNC’s sustainability in the host country.

H₁: There exists no relationship between employee innovativeness and MNC’c sustainability in the host country.

To decide on the hypotheses, this study will use descriptive statistics to come up with a conclusion. The variable in this instance is innovativeness which is derived from finding the average of the responses in Q10. Sustainability in the question is indicated by the performance of the firm. High performance translated to better sustainability of the business.

Over time differences have been shown to exist between the views and preference between men and women (Williams & Best, 1994). The table below shows an independent samples t-test testing the existence of a difference between the mean of views on innovation’s role is furthering sustainability based on gender.

Table 6 Differences in innovation based on gender

From table 5 above, the null hypothesis of the test is rejected due to the value of the p-value of the F-statistic being greater than 0.05. The test static has a value of 0.558 and a p-value of 0.457. There exists no difference in the views on innovativeness about gender.

Innovation and views about innovation vary between different age groups. It is important to check for the existence of differences between the various age groups.

Table 7 ANOVA between age and innovation

From table 7 above, the F value is 2.934. This value has significance with a value of 0.25 which is below the 0.05 alpha level of confidence implying that there exists a significant difference in the views of people on innovativeness.

The table below shows the regression output for the relationship between age and views on the impact of innovativeness on sustainability

Table 8 Regression between age and innovativeness

From table 8, the relationship between the two variables can be represented by the equation y=-0.078x+3.622 where x is the age group and y is the likely view of the employee on innovativeness. The significance of the impact of age on views on innovativeness is 0.456 which is greater than 0.05. This implies that age has a significant influence on views on the impact of innovativeness on sustainability.

RQ 3: What is the role of HRM practices (leadership, motivation, collective decision making, and rewards) in promoting employee creativity and innovativeness?

H₀: There exists a relationship between HRM practices and employee creativity and innovation.

H₁: There exists no relationship between HRM practices and employee creativity and innovativeness.

Human resource management is responsible for the creation of a suitable environment for employees to work in (Ceylan, 2013). This environment can either be innovative friendly or do not support innovation. Most of the employees agree that the practices of the HR department affect the innovativeness and creativity of the employees. This implies that there exists a relationship between HRM practices and the innovativeness and creativity scores of the employees.

HRM categorizes employees based on their gender (Aaltio et al., 2014). It is crucial to check whether there exist any differences between the views of the employees on HRM’s role in fostering innovation and creativity among employees. The table below shows the independent samples t-test to determine whether any differences exist.

Table 9 Differences in views on HRM based on gender

From table 9 above, the test statistic us 0.555 and has a p-value of 0.458 which is greater than 0.05. This implies that there exist no differences in the views on the role of HRM in creating an environment suitable for innovation and creativity based on the gender of the employee.3

The table below shows the ANOVA test for the difference in views on the role of HR management in influencing innovation and creativity among employees.

Table 10 ANOVA for HRM

From table 10 above, the F-value of the test is 2.156 with 0.081 significance. The significance of the test is above 0.05 which is the alpha level of significance. This implies that there is no significant difference in views on HRM based on different age groups.

Table 11 below shows the regression output on the relationship between HRM and the age group of an employee.

Table 11: Regression for age and HRM

From table 11, the relationship between the views of HRM’s role in improving innovativeness among the employees is represented by the equation y=-0.054x+3.73 where x is the age group and y is the view. The significance of age in the test is 0.577 which is above 0.05. This implies that age has a significant influence on the views on the role of HRM in facilitating innovation and creativity among employees.

RQ 4: How does a creative and innovative workforce affect the competitiveness of an MNC in the host country?

H₀: There exists a relationship between MNC’s competitiveness and the creativity and innovativeness of the workforce.

H₁: There exists no relationship between MNC’s competitiveness and the creativity and innovativeness of the workforce.

Independent t-test

            Views on competitiveness induced by innovation and creativity of employees may present variations according to the gender of the employee. The table below shows the independent sample t-test for the difference in views based on the gender of the respondent.

Table 12. Differences in views on competitiveness based on gender

From table 12 above, the critical value of the test is -0.179 having a p-value of 0.906 which represented the significance. The test is carried out at the 5% confidence interval. The p-value is greater than 0.05 which implies that we reject the null hypothesis of the t-test. This in turn implies that the average views between men and women have no significant differences. A competitive advantage is created by innovation (Lengnick-Hall, 1992)

The table below shows the ANOVA test for differences in views on the role of innovation and creativity of the employees in creating a marketing advantage.

Table 13 ANOVA for age and competitiveness

From table 13 above, the f-value from the test is 1.898 with a significance of 0.118 which is greater than the 0.05 significance level. This implies that there exists no significant difference on the role of creativity and innovativeness in creating a marketing advantage.

The table below shows the output for the regression model between the role of creativity and innovativeness and views on creating a competitive advantage.

Table 14 Regression for age and competitiveness

From table 14, the relationship between age and the views on the role of innovation and creativity of employees in creating a competitive advantage is y=-0.056x+3.706, where x is the age group and y is the view. The significance of age on the views has a value of 0.563 which is greater than 0.05 implying that age influences the views on the role of innovation and creativity of employees in creating a competitive advantage.

References

Williams, J. E., & Best, D. L. (1994). Cross-cultural views of women and men. Psychology and culture, 191-196.

Aaltio, I., Salminen, H. M., & Koponen, S. (2014). Aging employees and human resource management–evidence of gender-sensitivity?. Equality, Diversity, and Inclusion: An International Journal.