Purpose: The purpose of this paper is to improve understanding of how different aspects of the national institutional environment may influence the extent of innovative entrepreneurial activities across countries. Several institutional and conductive factors affecting a country’s capacity to support innovative entrepreneurship are explored.Design/methodology/approach: Institutional theory is used to examine the national regulatory, normative, cognitive and conducive aspects that measure a country’s ability to support innovative entrepreneurship. A cross-national institutional profile is constructed to validate an entrepreneurial innovation model. The impacts of country-level national institutions on innovative entrepreneurial activity as measured by Global Entrepreneurship Monitor data are assessed through structural equation modeling.Findings: Knowledge about the influence of specific institutional aspects on innovative entrepreneurship, and hence of institutional structures within and across countries, is enhanced. For new innovative enterprises, conductive and regulatory aspects seem to matter most. All conductive factors have a significant and positive impact on entrepreneurial activity rates.Research limitations/implications: Results could support policy makers and practitioners in evaluating government policies’ effects on innovative entrepreneurship. Interventions should target both individual attributes and context. Future research could include longitudinal designs to measure the direction of causality.Practical implications: Aspects such as regulatory institutions, and conductive factors such as information communication technology use and technology adoption, are important for innovation entrepreneurship development.Originality/value: The literature on institutional theory and innovative entrepreneurship is highly limited. This study complements growing interest in empirical analysis of the effects of national institutions on innovative entrepreneurial activities and substantiates previous empirical work.

The reproduction number (R0) is vital in epidemiology to estimate the number of infected people and trace close contacts. R0 values vary depending on social activity and type of gathering events that induce infection transmissibility and its pathophysiology dependence. In this study, we estimated the probable outbreak size of COVID-19 clusters mathematically using a simple model that can predict the number of COVID-19 cases as a function of time. We proposed a mathematical model to estimate the R0 of COVID-19 in an outbreak occurring in both local and international clusters in light of published data. Different types of clusters (religious, wedding, and industrial activity) were selected based on reported events in different countries between February and April 2020. The highest R0 values were found in wedding party events (5), followed by religious gathering events (2.5), while the lowest value was found in the industrial cluster (2). In return, this will enable us to assess the trend of coronavirus spread by comparing the model results and observed patterns. This study provides predictive COVID-19 transmission patterns in different cluster types based on different R0 values. This model offers a contact-tracing task with the predicted number of cases, to decision-makers; this would help them in epidemiological investigations by knowing when to stop.

Landfill site selection is an essential aspect of sustainable solid waste management as it ensures that the waste generated by a community or region is disposed of in an environmentally friendly and safe manner. The approach for selecting landfill sites seeks to choose locations that provide the least risk to the environment and public health while still satisfying the demands of the local community. This research aims to use a multi-criteria assessment to determine a landfill location in Al-Balqa Governorate in Jordan to ensure that the chosen site meets the needs of all stakeholders while minimizing the negative impact on the environment and the community. This research developed a hierarchy structure to make landfill site selection decisions, which involves identifying parameters such as distance to surface water, land cover, distance from urban and rural areas, distance to roads, slope, and soil permeability. A rating system was used to evaluate each criterion, and weights were assigned to reflect their relative importance. An overlay weighting technique was then used to assess site suitability based on expert opinions from related fields. In this studied area, about 204,283 m² is required to address 25 years of municipal solid waste volume, whereas this technique identified around 79,210,000 m² of potential landfill sites. Overall, the research highlights the importance of using a multi-criteria assessment approach for landfill site selection to ensure that the chosen site meets the needs of all stakeholders while minimizing negative impacts on the environment and public health. The study provides insights that can be useful for decision-makers involved in sustainable solid waste management in Jordan and other similar regions. -How to Find the suitable landfills to achieve sustainable development.-What aspects and criteria were comsidered in choosing the landfill site.

Purpose: The purpose of this paper is to explore the results of implementing the Kaizen approach in a caravan repairing project near the Jordanian–Syrian border in the Zaatari camp. Design/methodology/approach: The study is based on the exploratory qualitative research approach. The data were collected through interviews and on-site observation with employees who were involved with the caravan maintenance project and have adequate knowledge and information about this project. In this process, a fishbone diagram, a quality control tool, is used to recognize and explain a causal-effect relationship under the selected Kaizen theme. Findings: The findings suggest that the Kaizen approach was economical in terms of both money and time. Also, waste elimination can be achieved through a variety of tools and easily combined with the Kaizen approach. Implementing the Kaizen approach is an effective and reliable system that allows for the tackling of all types of inefficiencies in the caravan repairing project. Research limitations/implications: The findings of this study will help policy makers and managers put together suitable and effective policies that will assist those firms in overcoming the demands of customers and competitors to deliver high quality, inexpensive products in less time through the application of the Kaizen approach. This, in turn, will lead to improved quality, efficiency and productivity in the most cost-effective way. However, these results should not be generalized since they are only confined to the context of caravan repairing project. Originality/value: Very little research has been done that takes into account the contexts of developing countries. Additionally, most literature presents the use of Kaizen applications only in the manufacturing or production sectors. This study is the first to implement Kaizen as a continuous improvement technique in a caravan repairing project – a job shop industry different from the repetitive batch work environment that is usually associated with implementation of Kaizen. The current research should be of great interest to researchers, managers and professionals who wish to apply Kaizen approach as it is sustainable over time in similar projects.

As the COVID-19 pandemic has afflicted the globe, health systems worldwide have also been significantly affected. This pandemic has impacted many sectors, including health in the Kingdom of Jordan. Crises that put heavy pressure on the health systems shoulders include the emergency departments (ED), the most demanded hospital resources during normal conditions, and critical during crises. However, managing the health systems efficiently and achieving the best planning and allocation of their EDs resources becomes crucial to improve their capabilities to accommodate the crisiss impact. Knowing critical factors affecting the patient length of stay prediction is critical to reducing the risks of prolonged waiting and clustering inside EDs. That is, by focusing on these factors and analyzing the effect of each. This research aims to determine the critical factors that predict the outcome: the length of stay, i.e., the predictor variables. Therefore, patients length of stay in EDs across waiting time duration is categorized as (low, medium, and high) using supervised machine learning (ML) approaches. Unsupervised algorithms have been applied to classify the patients length of stay in local EDs in the Kingdom of Jordan. The Arab Medical Centre Hospital is selected as a case study to justify the performance of the proposed ML model. Data that spans a time interval of 22months, covering the period before and after COVID-19, is used to train the proposed feedforward network. The proposed model is compared with other ML approaches to justify its superiority. Also, comparative and correlation analyses are conducted on the considered attributes (inputs) to help classify the LOS and the patients length of stay in the ED. The best algorithms to be used are the trees such as the decision stump, REB tree, and Random Forest and the multilayer perceptron (with batch sizes of 50 and 0.001 learning rate) for this specific problem. Results showed better performance in terms of accuracy and easiness of implementation.

This study sought to determine the impact of implementing the energy management system ISO 50001 on the Zai Water Treatment Plant's energy efficiency performance and demonstrate how this implementation affected the cost and rate of energy consumption. The proposed study model contained three dependent variables—energy consumption, energy efficiency, and the cost of energy consumption. It also contained an independent variable—the energy management system ISO 50001. All these variables were used to develop various questions to help accomplish the study's goals. Planning was done by selecting pumping stations, selecting the most energy-consuming type of pump, and finally, choosing a pump maintenance project to improve energy performance. The researcher used the case of the Zai water pumping station as an example where the ISO 50001 energy management system was applied along with the stages of the Deming Cycle of management. Four pumping units from the Zai water pumping station served as the research sample for the study.