The study aimed at exploring the impact of three smart innovative solutions, i.e., Internet-of-Things, Big Data Analytics, and Cloud Computing on supply chain performance. Collecting data by questionnaires administered to a sample consists of supply chain managers of industrial firms. The results pointed out that these three smart solutions significantly and positively lift firms’ supply chain performance. That is, the hypotheses that Internet-of-Things, Big Data Analytics, and Cloud Computing have significant impacts on supply chain performance were supported. Therefore, the study concluded that for industrial firms to improve supply chain performance, such smart solutions should be assessed and applied. The study contributes to both academics and practitioners through providing empirical results on concurrent impacts of three advanced technologies in supply chain management context.

The aim of this study is to identify the effect of supply chain resilience as measured by supply chain flexibility, supply chain collaboration, and supply chain agility on supply chain performance. A sample consisting of employees from chemical industrial companies in Jordan was selected to collect data using an electronic questionnaire. Analyzing data via SmartPLS 3.0, the results showed that supply chain collaboration and supply chain agility as key dimensions of supply chain resilience had significant effects on supply chain performance, while supply chain flexibility exerted insignificant effect on supply chain performance. Therefore, managers are recommended to improve their firms’ abilities to carry out effective work with partners and to enhance firms’ abilities to respond quickly to unpredictable changes. Scholars are also requested to conduct further studies such as investigating the effect of supply chain redundancy on supply chain performance.

The aim of this research is to examine the impact of supply chain management through social media on competitiveness of the private hospitals in Jordan. The population of the study includes managers in various administrative disciplines. Therefore, the complete census method was used in this research to collect the primary data, where the total responses were 438 responses were used for analysis. The questionnaire was used as a basic instrument in the current research, as it was designed electronically through Google Forms and sent to the research sample via email. AMOS software was used to test the research hypotheses. The results showed that all dimensions of supply chain management through social media had a positive impact on competitiveness; the greatest effect was for strategic relations with suppliers. Based on the study results; managers at the examined companies should enhance their usage of social media with suppliers, according to the report, in order to support strategic connections with them.

The goal of the study was to determine the influence of green supply chain management strategies on performance in Jordanian industrial enterprises using just in time. All of Jordan's manufacturing enterprises were included in the analysis. A total of 218 companies were selected from the manufacturing industry. The study hypotheses were tested using Path Analysis. The results showed that green supply chain practices had a significant indirect effect on performance through JIT. Based on the study findings, the researchers recommend individuals and decision-makers to improve the expected results of green supply chain practices in the performance of economic and social business through just in time production and increasing the interest in logistics services as one of managing green supply chains practices in these companies.

The study aim is to examine the impact of industry 4.0 on sustainability of industrial organizations in Jordan. The population of the study consists of employees at various administrative levels of industrial organizations in Jordan. Due to the large population and the spatial and temporal limitations of the research, it was difficult to collect data using the comprehensive method. Therefore, the random sampling method was applied to collect data from the research population. The structural equation modeling (SEM) technique was used to test the impact of industry 4.0 dimensions on sustainability. The study results confirmed that all dimensions of industry 4.0 had an impact on sustainability. The greatest effect was for cyber-physical systems. Based on this result, researchers recommend the management of industrial organizations to invest in information technology to provide a large variety of data in a very short time and providing appropriate programs for analyzing big data and producing accurate and reliable information that can be used by employees.

The aim of the research is to test the impact of big data on the quality of decision making. The necessary data was collected from telecommunication companies operating in Jordan. Three companies provide telecommunications services in Jordan: Zain, Umniah, and Orange. Non-probability purposive sampling was used. Hence, the study instrument was distributed to managers at the senior and middle levels of these companies. The structured equation modeling (SEM) technique was employed to test the study hypotheses. The results confirmed that big data impacts decision quality. Besides, it was determined that the highest impact was on velocity. The researchers suggest that Jordanian telecom companies invest in information technology that allows them to provide data with accuracy, reliability, and high quality, as well as improve the qualifications of their employees.

The purpose of this research is to look into the drivers that influence whether or not users will use e-training. The research identified six elements that influence e-training intention to use: perceived ease of use (PEU), computer and internet self-efficacy (CIS), perceived usefulness (PUS), interaction (INT), technical support (TEC), and management support (MGS). Data were collected using a questionnaire distributed to a sample consisting of employees in private universities to test six hypotheses related to these factors. The results showed that four of these factors, i.e., perceived ease of use (PEU), computer and internet self-efficacy (CIS), perceived usefulness (PUS), and technical support (TEC) are key drivers of e-training intention to use. Results are discussed and conclusion is reported.