Age is there a difference between age groups?

Age is conceptualized as an important variable. The thesis predicts that there are differences in the level of perceived employability and perceived threat of ridesharing between age groups. It was mentioned that the variable age has been recoded into two groups: “young” and “less young”. This enables an independent samples t-test. This statistical test compares the means of two independent groups - in this case, between young and less young participants. It is used to determine whether or not there is a statistically significant difference between the two groups. H2a states: “Older taxi drivers in Romania are less concerned with the threat of ridesharing than younger taxi drivers in Romania”. For this hypothesis to stand true, there has to be a significant difference between the two age groups with regards to the threat of ridesharing.

In order to enable statistical analysis, some central conditions have to be met. The first requirement is that the dependent variable is continuous. In other words, the dependent variable is required to have a measurement level of either interval or ratio level. In this case, the dependent variable is measured at the interval level, which meets the criteria. The second requirement is that the independent variable is a binary or categorical variable. Indeed, the variable age has been re-coded as a categorical variable and, in turn, fulfills this requirement. The third central requirement is that the independence of observations. This means that the individuals in the first group cannot be in the second group. The variable passed this requirement as well. Ideally, a random sample would have been selected but the data collection strategy could

not fulfill this assumption. Therefore, it is impossible to state that the sample data from the population is random.

Figure 19 (p.30) presents the t-statistic of every independent samples t-test that was conducted within the thesis. As can be observed, with a t-statistic score of .954 and a two-tailed significance level of .348, there is no observed significant difference in the mean value of the perceived threat of ridesharing between the two age groups. The younger age group had a mean value of ridesharing threat of 3.553, whereas the older group reported a mean value of 3.911, implying that the direction is opposite to the hypothesised direction. In turn, H2a is rejected.

Furthermore, H2b states: “Older taxi drivers in Romania perceive themselves as more

employable than younger taxi drivers in Romania”. For this hypothesis to stand true, I need to find a statistically significant difference in the mean values of perceived employability across the two age groups. Again, some central assumptions have to be met. It was already stated that the independent variable age passes the categorical measurement level requirement. Furthermore, the dimension of perceived employability was operationalized as a scale, which has an inherently interval measurement level, which passes the continuous measurement level requirement of the dependent variable.

Figure 19 (p.30) presents the t-statistic score of the independent samples t-test which measures the differences in the mean level of perceived employability between the two age groups. With a t-statistic score of 2.028, there seems to be at least some difference in the mean score of the dependent variable between the two groups. Surprisingly, the younger group reported a mean value of perceived employability of 3.897, whereas the older group reported a mean value of 3.259. Again, this implies a negative relationship between age and perceived employability, which goes against the direction hypothesised in H2b. However, with a significance level of .052, the statistical test missed the required critical value for statistical significance. To this extent, H2b is also rejected.

Nevertheless, there is an observed difference between the level of perceived employability between age groups. It is possible that, with a substantially higher sample size, the results would have been significant. However, given the current results, the null hypothesis is accepted.

Furthermore, I wanted to test whether or not there is a significant difference between the two age groups with regards to other central variables, namely the effect of ridesharing, as well

as ridesharing preference and taxi preference. As can be seen from Figure 19 (p.30), there is a statistically significant difference between age groups in the case of the effect of ridesharing as well as well as ridesharing preference. Indeed, the difference in ridesharing effect is significant at .05, whereas ridesharing preference is even stronger, as it is significant at a critical value of .01.

Regarding the effect of ridesharing, the younger age group reported a mean value of 3.666, whereas the older group reported a mean value of 2.666. With a t-statistic score of 2.853, this negative relationship is significant at the 95% confidence interval level.

Regarding ridesharing preference, the younger age group reported a mean value of 3.676, whereas the older group reported a mean value of 2.410. Again, with a t-statistic value of 3.495 this negative relationship is significant at the 99% confidence interval level. Indeed, younger taxi drivers seem to prefer working through ridesharing services more than older taxi drivers.