International Projects and Cross-Cultural Adjustment of British Expatriates in Middle East: A Qualitative Investigation of Influencing Factors

Increased globalisation within the British AEC (Architectural, Engineering and Construction) sector has increased the need for companies to transfer staff to manage their overseas operations. To be able to perform abroad, expatriates must harmonise themselves to the conditions prevailing in the host country. These include getting accustomed to living, working and interacting with the host country nationals. The process is commonly referred to as 'cross-cultural adjustment'. Various factors influence the process of adjustment. In order to identify these issues, a qualitative study was undertaken, which mainly comprised of comprehensive literature review, individual interviews and focus group discussion with British expatriates working on international AEC assignments in Middle Eastern countries. Through interpretative approach, the current study aims to understand the concept of cross-cultural adjustment of British Expatriates based in Middle East and their influencing factors.

The findings suggest that success of expatriation does not entirely rest on an expatriate's ability but also on organisational support and assistance that expatriates receive prior to and during the assignment. Organisational factors such as selection mechanisms, job design, training, logistical and social support, mentoring, etc., influence various facets of expatriate adjustment. Striking cultural contrasts between British and Arab culture both in work and non work situations also dictate the level of support required by the expatriate, suggesting that relocation to less developed, remote or politically unstable regions, demands additional support and consideration by the parent company. This study is relevant to the AEC companies employing British expatriates, who need to be cognisant of the issues highlighted above to make rational and informed decisions when handling international assignments in the Middle East.

Cost-Directed Refactoring for Parallel Erlang Programs

This paper presents a new programming methodology for introducing and tuning parallelism in Erlang programs, using source-level code refactoring from sequential source programs to parallel programs written using our skeleton library, Skel. High-level cost models allow us to predict with reasonable accuracy the parallel performance of the refactored program, enabling programmers to make informed decisions about which refactorings to apply. Using our approach, we demonstrate easily obtainable, significant and scalable speedups of up to 21 on a 24-core machine over the sequential code.

Cataract extraction and patient vision-related quality of life: a cohort study

Aims: Cataract surgery is one of the most common surgeries performed, but its overuse has been reported. The threshold for cataract surgery has become increasingly lenient; therefore, the selection process and surgical need has been questioned. The aim of this study was to evaluate the changes associated with cataract surgery in patient-reported vision-related quality of life (VR-QoL).

Methods: A prospective cohort study was conducted. Consecutive patients referred to cataract clinics in an NHS unit in Scotland were identified. Those listed for surgery were invited to complete a validated questionnaire (TyPE) to measure VR-QoL pre- and post-operatively. TyPE has five different domains (near vision, distance vision, daytime driving, night-time driving, and glare) and a global score of vision. The influence of pre-operative visual acuity (VA) levels, vision, and lens status of the fellow eye on changes in VR-QoL were explored. 

Results: A total of 320 listed patients were approached, of whom 36 were excluded. Among the 284 enrolled patients, 229 (81%) returned the questionnaire after surgery. Results revealed that the mean overall vision improved, as reported by patients. Improvements were also seen in all sub-domains of the questionnaire.

Conclusion: The majority of patients appear to have improvement in patient-reported VR-QoL, including those with good pre-operative VA and previous surgery to the fellow eye. VA thresholds may not capture the effects of the quality of life on patients. This information can assist clinicians to make more informed decisions when debating over the benefits of listing a patient for cataract extraction.

Accumulating research: a systematic account of how cumulative meta-analyses would have provided knowledge, improved health, reduced harm and saved resources

BACKGROUND: "Cumulative meta-analysis" describes a statistical procedure to calculate, retrospectively, summary estimates from the results of similar trials every time the results of a further trial in the series had become available. In the early 1990 s, comparisons of cumulative meta-analyses of treatments for myocardial infarction with advice promulgated through medical textbooks showed that research had continued long after robust estimates of treatment effects had accumulated, and that medical textbooks had overlooked strong, existing evidence from trials. Cumulative meta-analyses have subsequently been used to assess what could have been known had new studies been informed by systematic reviews of relevant existing evidence and how waste might have been reduced.

METHODS AND FINDINGS: We used a systematic approach to identify and summarise the findings of cumulative meta-analyses of studies of the effects of clinical interventions, published from 1992 to 2012. Searches were done of PubMed, MEDLINE, EMBASE, the Cochrane Methodology Register and Science Citation Index. A total of 50 eligible reports were identified, including more than 1,500 cumulative meta-analyses. A variety of themes are illustrated with specific examples. The studies showed that initially positive results became null or negative in meta-analyses as more trials were done; that early null or negative results were over-turned; that stable results (beneficial, harmful and neutral) would have been seen had a meta-analysis been done before the new trial; and that additional trials had been much too small to resolve the remaining uncertainties.

CONCLUSIONS: This large, unique collection of cumulative meta-analyses highlights how a review of the existing evidence might have helped researchers, practitioners, patients and funders make more informed decisions and choices about new trials over decades of research. This would have led to earlier uptake of effective interventions in practice, less exposure of trial participants to less effective treatments, and reduced waste resulting from unjustified research.

Non-parametric bill of quantities estimation of concrete road bridges' superstructure: an artificial neural networks approach

Bridge construction responds to the need for environmentally friendly design of motorways and facilitates the passage through sensitive natural areas and the bypassing of urban areas. However, according to numerous research studies, bridge construction presents substantial budget overruns. Therefore, it is necessary early in the planning process for the decision makers to have reliable estimates of the final cost based on previously constructed projects. At the same time, the current European financial crisis reduces the available capital for investments and financial institutions are even less willing to finance transportation infrastructure. Consequently, it is even more necessary today to estimate the budget of high-cost construction projects -such as road bridges- with reasonable accuracy, in order for the state funds to be invested with lower risk and the projects to be designed with the highest possible efficiency. In this paper, a Bill-of-Quantities (BoQ) estimation tool for road bridges is developed in order to support the decisions made at the preliminary planning and design stages of highways. Specifically, a Feed-Forward Artificial Neural Network (ANN) with a hidden layer of 10 neurons is trained to predict the superstructure material quantities (concrete, pre-stressed steel and reinforcing steel) using the width of the deck, the adjusted length of span or cantilever and the type of the bridge as input variables. The training dataset includes actual data from 68 recently constructed concrete motorway bridges in Greece. According to the relevant metrics, the developed model captures very well the complex interrelations in the dataset and demonstrates strong generalisation capability. Furthermore, it outperforms the linear regression models developed for the same dataset. Therefore, the proposed cost estimation model stands as a useful and reliable tool for the construction industry as it enables planners to reach informed decisions for technical and economic planning of concrete bridge projects from their early implementation stages.

A realistic evaluation of track and trigger systems and acute care training for early recognition and treatment of deteriorating ward-based patients: research protocol.

Aim The aim of the study is to evaluate factors that enable or constrain the implementation and service delivery of early warnings systems or acute care training in practice. Background To date there is limited evidence to support the effectiveness of acute care initiatives (early warning systems, acute care training, outreach) in reducing the number of adverse events (cardiac arrest, death, unanticipated Intensive Care admission) through increased recognition and management of deteriorating ward based patients in hospital [1-3]. The reasons posited are that previous research primarily focused on measuring patient outcomes following the implementation of an intervention or programme without considering the social factors (the organisation, the people, external influences) which may have affected the process of implementation and hence measured end-points. Further research which considers the social processes is required in order to understand why a programme works, or does not work, in particular circumstances [4]. Method The design is a multiple case study approach of four general wards in two acute hospitals where Early Warning Systems (EWS) and Acute Life-threatening Events Recognition and Treatment (ALERT) course have been implemented. Various methods are being used to collect data about individual capacities, interpersonal relationships and institutional balance and infrastructures in order to understand the intended and unintended process outcomes of implementing EWS and ALERT in practice. This information will be gathered from individual and focus group interviews with key participants (ALERT facilitators, nursing and medical ALERT instructors, ward managers, doctors, ward nurses and health care assistants from each hospital); non-participant observation of ward organisation and structure; audit of patients' EWS charts and audit of the medical notes of patients who deteriorated during the study period to ascertain whether ALERT principles were followed. Discussion & progress to date This study commenced in January 2007. Ethical approval has been granted and data collection is ongoing with interviews being conducted with key stakeholders. The findings from this study will provide evidence for policy-makers to make informed decisions regarding the direction for strategic and service planning of acute care services to improve the level of care provided to acutely ill patients in hospital. References 1. Esmonde L, McDonnell A, Ball C, Waskett C, Morgan R, Rashidain A et al. Investigating the effectiveness of Critical Care Outreach Services: A systematic review. Intensive Care Medicine 2006; 32: 1713-1721 2. McGaughey J, Alderdice F, Fowler R, Kapila A, Mayhew A, Moutray M. Outreach and Early Warning Systems for the prevention of Intensive Care admission and death of critically ill patients on general hospital wards. Cochrane Database of Systematic Reviews 2007, Issue 3. www.thecochranelibrary.com 3. Winters BD, Pham JC, Hunt EA, Guallar E, Berenholtz S, Pronovost PJ (2007) Rapid Response Systems: A systematic review. Critical Care Medicine 2007; 35 (5): 1238-43 4. Pawson R and Tilley N. Realistic Evaluation. London; Sage: 1997

Identifying the Impact of Incomplete Datasets on Process Cycle Time Prediction in an Aerospace Assembly Line

Supply Chain Simulation (SCS) is applied to acquire information to support outsourcing decisions but obtaining enough detail in key parameters can often be a barrier to making well informed decisions.
One aspect of SCS that has been relatively unexplored is the impact of inaccurate data around delays within the SC. The impact of the magnitude and variability of process cycle time on typical performance indicators in a SC context is studied.
System cycle time, WIP levels and throughput are more sensitive to the magnitude of deterministic deviations in process cycle time than variable deviations. Manufacturing costs are not very sensitive to these deviations.
Future opportunities include investigating the impact of process failure or product defects, including logistics and transportation between SC members and using alternative costing methodologies.