The research purposed in this paper is to investigate the impact of the health information technology on hospital performance through the health information quality as mediating variable, as new evidence from the teaching hospitals in the north of Jordan. Research design and methodology approach based on a survey that is conducted to collect the requested data to develop a model connect between the health information technologies, health information quality and hospital performance by using the Structural Equation Modeling approach. The research findings show that there is an intertwined and reciprocal relation between Health Information Technologies (HITs), hospital performance, and health information quality. HITs have direct positive impacts on both hospital performance and health information quality. Health information quality has also a direct impact on hospital performance. Besides, health information quality functioned as a partial mediator between HITs and hospital performance. The study did not examine the factors that influence the relationship between HITs, hospital performance and health information quality. This paper is evidence for the investor in the healthcare sector to invest more in HITs and health information quality, where the expected results are productivity improvement, performance leveraging and error reduction. The research originality is to introduce new evidence support literature form the Middle East countries is the main contribution of this paper.

Military aviation inventory management systems are a vital tool for air forces to reduce operating costs whilst improving fleet readiness, aircraft serviceability, and availability, and the safety measurements of the country. This paper aims to establish a local, affordable, high quality, reliable, and adaptive inventory management system which manages and improves inventory in the military aviation industry (Air forces). The aim of the new system is to improve aircraft fleet serviceability, reliability, and readiness in order to enhance the operational status and level of readiness at the least possible costs. This study designs, proposes, and implements a highly reliable customized Microsoft Access software as a powerful, simple, user-friendly. Affordable software that supports the on-time availability of the air force inventory of spare parts. The system will have full capability of integrating maintenance management systems (M.M.S.) and will address aircraft inventory challenges. The proposed system provides high-quality reports that improve supply chain management and processes that help collate maintenance, supply chain, and logistics information that reduces stock to the minimum. This will result in improved components, increased serviceability, availability, and reliability, decreased costs, and decreased Aircraft on Ground (A.O.G.).

Purpose: These days vehicles' spare parts (SPs) are a very big market, and there is a very high demand for these parts. Forecasting vehicles' SPs price and demand are difficult because of the lack of data and the pricing of the SPs is not following the normal value chain methods like normal products.Design/methodology/approach: A proposed model using multiple linear regression was developed as a guide to forecasting demand and price for vehicles' SPs. A case study of selected hybrid vehicle is held to validate the results of the research. This research is an original study depending on quantitative and qualitative methods; some factors are generated from realistic data or are calculated using numerical equations and the analytic hierarchy process (AHP) method; online questionnaire and expert interview survey.Findings: The price and demand for SPs have a linear relationship with some independent variables is the hypothesis that is tested. Even though the proposed models are generally recommended for predicting demand and price, in this research the linear relationship models are not significant enough to calculate the expected price and demand.Originality/value: This research should concern both academics and practitioners since it provides new intuitions on the distinctions between scientific and industrial world regarding SPs for vehicles as it is the first study that investigates price and demand of vehicles' SPs.

Lean implementation in the service sector has a dilemma related to defining the gap of the lean system and identifying the flaws in the processes which affect the overall performance and efficiency. This paper presents an innovative model that can help service companies to improve lean implementation and integrate appropriate Key Performance Indicators (KPIs) with the strategic goals. The aim of this paper is to also investigate different forms of waste that affect services performance by using the data of a global best practice. It also aims to apply and integrate the KPIs with Lean Management Tools to overcome the potential limitations of the traditional ones. As a first step of improvement, designing a new KPI lean method can lead to determining and reducing all different forms of existing wastes. Furthermore, such a method is expected to (i) improve the existing processes; (ii) enhance performance, (iii) increase time efficiency; and (iv) improve work accuracy. A new model that focuses on low-performance processes has been designed. The proposed model is also used to develop KPIs that are measurable and capable of detecting flaws and identify the possible improvements. When the model is continuously applied by service providers, the waiting time and non-adding value activities are expected to be significantly minimized. Likewise, monitoring and control of internal processes and activities can be improved. Furthermore, lean management is advantageous for the telecommunication sector as it allows a quick response to rapid changes in the telecom technology and, thus, improves the customer satisfaction.

A new dynamic assessment algorithm based on the Type-1 Fuzzy Logic System (T1FLS) is proposed in this research work to develop a dynamic warehouse assessment scheme. First, the criteria and the sub-criteria that affect a warehouse performance are identified and, then, classified into a number of clusters. Second, the warehouse performance score is determined by employing the T1FLS that is developed by using expert knowledge and/or digital data. The data for the new assessed warehouses are then evaluated to ensure that the new data are not redundant and, thus, can lead to meaningful information. Finally, such new data are utilized to dynamically update the T1FLS. The algorithm has been validated on a series of actual warehouses in Jordan, and it has been shown that the presented scheme can successfully assess the warehouses with respect to the identified criteria. In addition to being dynamic, the newly proposed assessment framework can take into consideration uncertainties naturally, this being due to fuzzy logic which has the ability to model them intrinsically via the concept of vagueness.