Abstract
The term Dynamic Manufacturing Network (DMN) refers to a new collaborative business model that relies on real-time information sharing, synchronized planning and common business processes. DMNs are operational networks formed among autonomous and globally dispersed partners, and can be seen as the manufacturing industry application of the Virtual Enterprise (VE) concept. Despite their numerous practical benefits such as optimized processes and access to new and global markets, they are particularly vulnerable to disruptions. Any disruption in manufacturing or transportation of products may obviously result in failed orders, thus impacting the whole DMN reliability. Instead of developing stochastic models to deal with uncertainty, as it is usually done, we have rather integrated the concept of flexibility into the tactical and operational planning of such networks. We therefore propose in this work, a multi-objective optimization model that simultaneously maximizes reactive flexibility measures while minimizing total operating costs.

Abstract
A Dynamic Manufacturing Network (DMN) is the manufacturing industry application of the Virtual Enterprise (VE) business model based on real time information sharing and process integration. DMNs are normally formed and supported by a collaborative platform previously designed and built by a preexisting strategic partnership. The collaborative platform forms and tracks each DMN through all phases of its life cycle which leads to the accumulation and storage of large historical datasets on partner and customer characteristics and actions. This data holds the key to customer and manufacturer behavioral patterns and performances that can further be used in the decision making processes. In this study, we have focused on tackling this widely neglected research opportunity, by integrating manufacturer, order and customer data and characteristics into DMN formation and planning. The developed big data analytics approach consists of TOPSIS, fuzzy inference system and multi objective optimization techniques. Initially, by integrating the TOPSIS multi criteria decision making technique with a fuzzy inference system (FIS) we have computed indices for Manufacturer reliability and Order priority. Then we developed a multi-objective mixed integer linear programming (MILP) model to generate efficient solutions minimizing cost and assigning more reliable manufacturers to orders with higher priority.

Abstract
BackgroundUnderstanding the perceived importance of Patient-Centered Care (PCC) among Palestinian doctors and how the provider and other clinical characteristics may impact their views on PCC is essential to determine the extent to which PCC can be implemented. This study investigates the provision of PCC among hospital doctors in a developing and unstable country, namely, Palestine.MethodsThis descriptive, cross-sectional research employed self-report survey among 369 Palestinian doctors working in hospitals in 2016. Respondents completed the Provider-Patient Relationship Questionnaire (PPRQ) and were asked to rate the importance of 16 PCC subjects in a context-free manner. Then they scored the existence of eight contextual attributes in their workplace.ResultsAlthough 71.4% of the participants got training in communication, only 45% of the participants knew about PCC. 48.8% of doctors considered the exchange of information with patients most important PCC component. Clustering identified three groups of doctors: 32.4% of doctors reported good perceptions of PCC, 47.5% moderate; and 20.1% poor. Older, married, and specialist doctors and those familiar with PCC are more likely classified in the good cluster. Results revealed a significant difference between doctors' views based on their gender, experience, marital status, previous knowledge about PCC, and type of hospital in favor of males, experienced, married, familiar with PCC, and doctors in private hospital respectively. The level of job interest, nurses' cooperation, the tendency of patients to hide information, and doctor's friendly style were positively related with more perceived importance of PCC.ConclusionWe identified benchmark doctors who perceive the high relative importance of PCC. Our results highlighted knowledge gaps and training weaknesses among doctors in public and private hospitals in respect to their views on PCC. Decision makers may invest in the determined contextual predictors to enhance attitudes towards PCC. This work doesn't address patients' views on PCC.

Abstract
BackgroundThe structure, function, and capacity of the health care system in the Occupied Palestinian Territories (OPT) had been largely shaped by the complex political history of the country. Since the establishment of the Palestinian Authority in 1994, the reform efforts were subsidized much by the international aids to rebuild the country's institutional capacity. No previous studies have provided a realistic evaluation of Palestinian achievements in the conduct of public healthcare, we examine the relative productive efficiency of public hospitals (their managers' success in the usage of resources) during 2010-2015 within West Bank and Jordan. Then, we estimate the efficiency of policies within which managers operate (the program efficiency) across the two countries.MethodsWe employ the Data Envelopment Analysis (DEA) models to distinguish between within-country managerial efficiencies and public policy program efficiencies across the two countries. The study follows two key steps, the first step evaluates managerial efficiencies and explores trends in performance within each country. Then, we examine the program efficiencies across the two countries.ResultsPublic hospitals improved their year-specific overall efficiency from 75 to 80% in the West Bank and from 78 to 86% in Jordan in 2010 and 2015 respectively. Changes in efficiency are driven by scale effects in West Bank and by managerial enhancements in Jordan. Program efficiency in West Bank outperformed Jordan during 2010-2012, there was no significant difference in mean program efficiencies between the two countries during 2013-2015.ConclusionsThis work addresses a gap in the DEA literature by empirically investigating the efficiency of public hospitals as distinct from program efficiency in a developing country, namely, Palestine. Findings stimulate hospital managers to enhance potential improvements, policymakers to allocate resources, and international donors to focus on the right adoption of new technology to get better benefits from their considerable investments in public hospitals.

Abstract
This paper describes the process of formulation and validation of a synthetic risk network model for the Brazilian military shipbuilding industry. This model is composed of risk events and their potential causes that will be the basis of the process of identification and analysis of future risks on similar projects. This process involved an extensive literature review to collect and list an initial catalogue of risks, causes and related effects, followed by an analysis to summarise and schematically group the risks. Then, the Delphi method with a panel of experts from the Brazilian Navy was used to analyse and assess the proposed model.

Abstract
Background: While health needs and expenditure in the Occupied Palestinian Territories (OPT) are growing, the international donations are declining and the economic situation is worsening. The purpose of this paper is twofold, to evaluate the productive efficiency of public hospitals in West Bank and to study contextual factors contributing to efficiency differences. Methods: This study examined technical efficiency among 11 public hospitals in West Bank from 2010 through 2015 targeting a total of 66 observations. Nationally representative data were extracted from the official annual health reports. We applied input-oriented Data Envelopment Analysis (DEA) models to estimate efficiency scores. To elaborate further on performance, we used Tobit regression to identify contextual factors whose impact on inefficient performance is statistically significant. Results: Despite the increase in efficiency mean scores by 4% from 2010 to 2015, findings show potential savings of 14.5% of resource consumption without reducing the volume of the provided services. The significant Tobit model showed four predictors explaining the inefficient performance of a hospital (p < 0.01) are: bed occupancy rate (BOR); the outpatient-inpatient ratio (OPIPR); hospital's size (SIZE); and the availability of primary healthcare centers within the hospital's catchment area (PRC). There is a strong effect of OPIPR on efficiency differences between hospitals: A one unit increase in OPIPR will lead a decrease of 19.7% in the predicted inefficiency level holding all other factors constant. Conclusion: To date, no previous studies have examined the efficiency of public hospitals in the OPT. Our work identified their efficiency levels for potential improvements and the determinants of efficient performance. Based on the measurement of efficiency, the generated information may guide hospitals' managers, policymakers, and international donors improving the performance of the main national healthcare provider. The scope of this study is limited to public hospitals in West Bank. For a better understanding of the Palestinian market, further research on private hospitals and hospitals in Gaza Strip will be useful. © 2018 The Author(s).