The aim of this research paper is to identify the effect of ERP successful implementation on employees' productivity, service quality and innovation. Data were collected via questionnaires from 129 employees working in the Jordanian telecommunication organizations. The collected data were analyzed using descriptive statistics and structural equation model to test the study hypotheses using AMOS 16.0. The results of this study revealed that there is a significant effect of organizational impact on employees' productivity, service quality and innovation. Whereas, satisfaction only affects the service quality and innovation of employees leaving the employee's productivity surprisingly not affected. This result is very likely due to the lack of suitable training. Therefore, one important recommendation is to develop a training course that identifies and explains to employees all the necessary changes that will occur to the business processes inside the organization as a result of the ERP implementation.

Prior research in several industries, particularly manufacturing industries, has confirmed the use of supply chain integration (SCI) to achieve green innovation (GI). Despite this, there has been very little research into the effects of SCI on the GI of manufacturing businesses. As a result, the current study was carried out to close this gap in the literature. Data from 231 manufacturing businesses in Jordan was used to validate a framework of several hypotheses about the relationships involving SCI and GI. SCI (customer integration (CI) and supplier integration (SI) have beneficial benefits on the green product and process innovation (GPDI & GPRI), according to the results of structural equation modeling. SI's effects on green products and process innovation are moderated by environmental unpredictability. The effects of CI on green product innovation are being moderated by environmental unpredictability. Environmental uncertainty, on the other hand, does not moderate the impacts of CI on green process innovation. This research adds to our knowledge of the SCI-GI link.

This paper investigates Algeria's main export volatility drivers via a regression model. The methodology involves the construction and estimation of an econometric model. In this model, the annual time series from 1992 to 2016 is used to estimate the impact of export structure and product concentration on the size of export volatility. The results reveal that export volatility in Algeria is high, and this is due to the growing percentage of consumer and raw material exports. The increasing size of exports is also an essential determinant of volatility. The findings indicate a need to reduce the reliance on primary exports while policymakers should diversify the export basket to reduce export volatility.

Academics and practitioners have become more interested in big data analytics (BDA) in recent years. There have been few empirical studies on the relationship between BDA and green supply chain management (GSCM), as well as the importance of environmental orientation (EO). A total of 128 responses from Jordanian industrial businesses were evaluated using the structural equation modeling method. The BDA, EO has a favorable and significant relationship with external and internal GSCM, according to the findings of this study. Furthermore, EO serves as a mediator between BDA and the external, and internal GSCM. The findings provide managerial insight into how to use BDA to establish a proactive environmental policy that covers all GSCM activities.

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