five

Hypotheses testing.

收藏
Figshare2021-06-11 更新2026-04-28 收录
下载链接:
https://figshare.com/articles/dataset/Hypotheses_testing_/14771581
下载链接
链接失效反馈
官方服务:
资源简介:
The arguable claims of levels of trust in politics and business situations motivated this study, which investigates the degree of trust within micro, small, and medium categories of Hungarian Information and Communication Technology (ICT) companies. Different sizes of companies have varying interactions between internal members and their business partners. This study concentrated on exploring Hungarian ICT companies due to their significant role in supporting Industry 4.0. The study population are active Hungarian ICT companies. This research implemented random cluster selection related to the location of ICT firms. It exploited 100 samples, including micro, small, and medium-sized companies, and implemented discriminant analysis to examine the description and hypotheses. First, this study found that the level of trust in institutions within micro, small, and medium-sized companies varies significantly. The level of trust in institutions proliferates within corporations due to the capability of the formal institution to provide fair public services. This research additionally underlined that the performance of the Hungarian government would improve trust amongst the companies. Second, this study concluded that the level of interpersonal trust within three categories of companies was similar. A high level of interpersonal trust would expand internal engagement among the members of companies. Finally, the level of trust in business partners varied significantly within the distinct sizes of Hungarian ICT companies. A high level of trust in corporate associates improves business collaboration, reduces uncertainty, and supports long-term business connections. Levels of institutional trust and inter-organizational trust differed amongst different categories of companies. However, the level of interpersonal trust remained similar within companies of the various sizes.
创建时间:
2021-06-11
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作