Estimated Results
Here, the ordered-probit estimated results on relationships between several firm characteristics as well as attitudes towards modern technologies. The main explanatory variables are the industry (retail, manufacturing, wholesale, ICT as well as other industries), spatial market space of the companies’ services or products (prefecture, the city as well as the globe), firm size (employees’ log number) and existence of unions and the employee composition.
The significant and positive coefficients in this result meant the characteristics were linked with the positive attitudes toward utilization of modern technology. This result shows that the bigger the size, the higher the employees’ level of education while the lower the employees’ age, the firms become increasingly active in using modern technology. It should be noted that coefficients for this ratio of the postgraduate education are bigger than those of the university graduates; this suggests that the skill threshold is complementary to using modern technology on a higher level.
Estimation was done by utilizing firm age (the years it has been established) as the additional explanatory variable through linking microdata with survey data of all the research. The firm age coefficient was found to be statistically insignificant while and size, as well as the level of significance of the employees’ age coefficient, remain unaffected. Therefore, the firms that employ the younger workers possess the positive attitude when it comes to utilizing modern technology irrespective of the age of the firm. Meanwhile, the female ratio coefficient is significant and positive at a 5 percent level. It is recommended that firms should consider it important to serve a broad range of the consumers in order to collect accurate information on consumers; needs and firms like these could be active when employing employees of the female gender and utilization of customer data.
The world market;s coefficient is highly significant and positive which confirms that globalized firms possess positive attitudes towards modern technology right after the rest of the firm characteristics. The ICT industry coefficients are highly significant and positive; however, the service industries coefficients are insignificant except for the wholesale industry which is marginally positively coefficient. Nonetheless, these insignificant differences translate to mean that the manufacturing, service and retail firms all maintain positive attitudes.
The estimated results that have been presented above through the use of cross-sectional data could not be translated as causality in the econometric sense. For instance, positive association between the employees; education and attitude towards the modern technologies might be the outcome of utilization of robotics and Artificial Intelligence by firms as well as the propensity towards hiring young employees that are highly educated. At the same time, the companies that use technology actively or Artificial Intelligence may expand their activities internationally which might have led in a positive relationship between the globalization as well as the positive attitudes towards the new technologies. Therefore, the tentative interpretation of the relationships that have been observed indicates bi-directional causality or complementarity.;
Lesson 1: Thesis Lesson 2: Introduction Lesson 3: Topic Sentences Lesson 4: Close Readings Lesson 5: Integrating Sources Lesson 6:…
Lesson 1: Thesis Lesson 2: Introduction Lesson 3: Topic Sentences Lesson 4: Close Readings Lesson 5: Integrating Sources Lesson 6:…
Lesson 1: Thesis Lesson 2: Introduction Lesson 3: Topic Sentences Lesson 4: Close Readings Lesson 5: Integrating Sources Lesson 6:…
Lesson 1: Thesis Lesson 2: Introduction Lesson 3: Topic Sentences Lesson 4: Close Readings Lesson 5: Integrating Sources Lesson 6:…
Lesson 1: Thesis Lesson 2: Introduction Lesson 3: Topic Sentences Lesson 4: Close Readings Lesson 5: Integrating Sources Lesson 6:…
Lesson 1: Thesis Lesson 2: Introduction Lesson 3: Topic Sentences Lesson 4: Close Readings Lesson 5: Integrating Sources Lesson 6:…