## 5 Analysis and Findings
### Exploratory Data Analysis
However, certain elements of Organizational Culture are slightly at odds with the intention to adopt green logistics, and Technological Readiness, while slightly associated with a higher intention to adopt green logistics, is not a strong enough factor to make a significant impact on its own. This highlights the complexity of factors influencing the adoption of green logistics and the need for a multifaceted approach to understanding and promoting it. To visualize the distribution of the variables, we used boxplots (a.k.a. box-and-whiskers plots), which are a common type of visual measure that displays the distribution of a continuous variable broken down by a categorical variable. Figures 3 and 4 show the boxplots for perceived benefits and Intention to adopt green logistics grouped by job role, respectively. The boxplots provided offer a comparison of the perceived benefits and intentions towards adopting green logistics among four distinct job roles: Operations Staff, Logistics Officer/Executive, Supervisor, and Manager. When considering the perceived benefits of job roles, the data reveals interesting insights across different dimensions. First, the range of responses varies significantly among the job roles. Operations Staff members display a wide range of perceptions about the benefits of green logistics, indicating either diverse opinions within the group or a lack of consensus on the topic. On the other hand, Logistics Officers/Executives have a somewhat narrower interquartile range (IQR), pointing towards a greater level of agreement on the benefits of green logistics within this group. Supervisors exhibit a range of perceived benefits similar to that of Logistics Officers/Executives, with a relatively tight IQR, while Managers show the broadest IQR, suggesting that perceptions of the benefits of green logistics vary widely among individuals in these roles. In terms of median values, all groups recorded medians above the midpoint of the scale. This suggests a general inclination towards acknowledging the benefits of green logistics across all job roles. Notably, Managers had a slightly higher median perceived benefit compared to other roles, which may indicate that, on average, individuals in managerial positions see greater benefits in green logistics. The analysis also highlighted the presence of outliers in each category, with Managers showing a particularly high number of individuals whose perceptions significantly deviate from the majority. This observation points to the existence of significantly different views on the benefits of green logistics, especially among those in managerial positions. The analysis of the intention to adopt green logistics by job role provides insights into the commitment levels across different positions within an organization. When considering the range of responses, Operations Staff members display a notably narrow range, indicating a more uniform belief or plan regarding the adoption of green logistics practices within this group. Logistics Officers/Executives exhibit a similar narrow range but with a higher median, suggesting a strong collective intention to adopt green logistics. Supervisors have an interquartile range comparable to that of Logistics Officers/Executives but with fewer outliers, indicating a more consistent intention among this group. Managers, on the other hand, show the broadest range, pointing to diverse intentions about adopting green logistics practices among individuals in this role. In terms of median values, the intention to adopt green logistics is consistent across job roles, being around the upper third of the scale. This suggests that, on average, respondents from each job role have a strong intention to engage in green logistics practices. However, the presence of outliers, particularly in the Operations Staff and Manager categories, indicates that there are individuals who may either be not as convinced of the benefits or are particularly motivated towards adopting green logistics practices.