جستجوی مقالات مرتبط با کلیدواژه « صنعت حمل و نقل بار جاده ای » در نشریات گروه « فناوری اطلاعات »

This research has been done with the aim of identifying and ranking the factors affecting the digital transformation strategy in Iran's road freight transportation industry, focusing on the Internet of Things and data analytics. After reviewing the literature, semi-structured interviews were conducted with 20 academic and road freight transportation industry experts in Iran, who were selected using the purposive sampling method and saturation principle. In the quantitative part, the opinions of 170 employees of this industry, who were selected based on Cochran's formula and stratified sampling method, were collected using a researcher-made questionnaire. Delphi technique, literature review and coding were used to analyze the data in the qualitative part. In the quantitative part, inferential statistics and SPSS and smartPLS software were used. Finally, 40 indicators were extracted in the form of 8 factors and ranking of indicators and affecting factors was done using factor analysis. The result of this research shows that the internal factors have the highest rank and software infrastructure, hardware infrastructure, economic, external factors, legal, cultural and penetration factor are in the next ranks respectively. Therefore, it is suggested that organizations consider their human resource empowerment program in line with the use of technology and digital tools.

The purpose of this research is to identify the drivers, obstacles and consequences of digital entrepreneurship in Iran's road freight transportation industry. The statistical society of this research in the qualitative part was made up of 20 experts in this field who were selected using theoretical saturation. In the quantitative part, using Cochran's formula and cluster sampling method, 170 employees of this industry were selected as samples. In order to collect data, a semi-structured interview was used in the qualitative part and a researcher-made questionnaire was used in the quantitative part, whose validity and reliability were checked and confirmed. In the data analysis, systematic literature review and coding and Maxqda software were used in the qualitative part, and inferential statistics and SPSS and Lisrel software were used in the quantitative part. Finally, 9 indicators in 4 driver factors, 11 indicators in 3 obstacle factors and 55 indicators in 8 consequence categories were extracted and prioritized using factor analysis. The result of this research shows that the political component is a priority as a driver and political obstacles are a priority as an obstacle. Therefore, the role of the government in this field is very important.