A profile of low vision services in England the Low Vision Service Model Evaluation (LOVSME) project

In the UK, low vision rehabilitation is delivered by a wide variety of providers with different strategies being used to integrate services from health, social care and the voluntary sector. In order to capture the current diversity of service provision the Low vision Service Model Evaluation (LOVSME) project aimed to profile selected low vision services using published standards for service delivery as a guide. Seven geographically and organizationally varied low-vision services across England were chosen for their diversity and all agreed to participate. A series of questionnaires and follow-up visits were undertaken to obtain a comprehensive description of each service, including the staff workloads and the cost of providing the service. In this paper the strengths of each model of delivery are discussed, and examples of good practice identified. As a result of the project, an Assessment Framework tool has been developed that aims to help other service providers evaluate different aspects of their own service to identify any gaps in existing service provision, and will act as a benchmark for future service development.

PCIM:a project control and inhibiting‐factors management model

In construction projects, the aim of project control is to ensure projects finish on time, within budget, and achieve other project objectives. During the last few decades, numerous project control methods have been developed and adopted by project managers in practice. However, many existing methods focus on describing what the processes and tasks of project control are; not on how these tasks should be conducted. There is also a potential gap between principles that underly these methods and project control practice. As a result, time and cost overruns are still common in construction projects, partly attributable to deficiencies of existing project control methods and difficulties in implementing them. This paper describes a new project cost and time control model, the project control and inhibiting factors management (PCIM) model, developed through a study involving extensive interaction with construction practitioners in the UK, which better reflects the real needs of project managers. A set of good practice checklist is also developed to facilitate implementation of the model. © 2013 American Society of Civil Engineers.

Benchmarking project management practices of Caribbean organizations using analytic hierarchy process

Effective management of projects is becoming increasingly important for any type of organization to remain competitive in today’s dynamic business environment due to pressure of globalization. The use of benchmarking is widening as a technique for supporting project management. Benchmarking can be described as the search for the best practices, leading to the superior performance of an organization. However, effectiveness of benchmarking depends on the use of tools for collecting and analyzing information and deriving subsequent improvement projects. This study demonstrates how analytic hierarchy process (AHP), a multiple attribute decision-making technique, can be used for benchmarking project management practices. The entire methodology has been applied to benchmark project management practice of Caribbean public sector organizations with organizations in the Indian petroleum sector, organizations in the infrastructure sector of Thailand and the UK. This study demonstrates the effectiveness of a proposed benchmarking model using AHP, determines problems and issues of Caribbean project management in the public sector and suggests improvement measures for effective project management.

Using a simulation model for knowledge elicitation and knowledge management

The work reported in this paper is part of a project simulating maintenance operations in an automotive engine production facility. The decisions made by the people in charge of these operations form a crucial element of this simulation. Eliciting this knowledge is problematic. One approach is to use the simulation model as part of the knowledge elicitation process. This paper reports on the experience so far with using a simulation model to support knowledge management in this way. Issues are discussed regarding the data available, the use of the model, and the elicitation process itself. © 2004 Elsevier B.V. All rights reserved.

Addressing the project implementation challenges in the Saudi Arabian power supply industry: an investigative approach towards improving project delivery

For many decades, the Kingdom of Saudi Arabia has been widely known for being a reliable oil exporter. This fact, however, has not exempted it from facing significant domestic energy challenges. One of the most pressing of these challenges involves bridging the widening electricity supply-demand gap where, currently, the demand is growing at a very fast rate. One crucial means to address this challenge is through delivering power supply projects with maximum efficiency. Project delivery delay, however, is not uncommon in this highly capital-intensive industry, indicating electricity supplies are not coping with the demand increases. To provide a deeper insight into the challenges of project implementation and efficient practice, this research adopts a pragmatic approach by triangulating literature, questionnaires and semi-structured interviews. The research was conducted in the Saudi Arabian power supply industry – Western Operating Area. A total of 105 usable questionnaires were collected, and 28 recorded, semi-structured interviews were conducted, analysed and synthesised to produce a conceptual model of what constitutes the project implementation challenges in the investigated industry. This was achieved by conducting a comprehensive ranking analysis applied to all 58 identified and surveyed factors which, according to project practitioners in the investigated industry, contribute to project delay. 28 of these project delay factors were selected as the "most important" ones. Factor Analysis was employed to structure these 28 most important project delay factors into the following meaningful set of 7 project implementation challenges: Saudi Electricity Company's contractual commitments, Saudi Electricity Company's communication and coordination effectiveness, contractors' project planning and project control effectiveness, consultant-related aspects, manpower challenges and material uncertainties, Saudi Electricity Company's tendering system, and lack of project requirements clarity. The study has implications for industry policy in that it provides a coherent assessment of the key project stakeholders' central problems. From this analysis, pragmatic recommendations are proposed that, if enacted, will minimise the significance of the identified problems on future project outcomes, thus helping to ensure the electricity supply-demand gap is diminished.

Web based expert elicitation of uncertainties in environmental model inputs

When constructing and using environmental models, it is typical that many of the inputs to the models will not be known perfectly. In some cases, it will be possible to make observations, or occasionally physics-based uncertainty propagation, to ascertain the uncertainty on these inputs. However, such observations are often either not available or even possible, and another approach to characterising the uncertainty on the inputs must be sought. Even when observations are available, if the analysis is being carried out within a Bayesian framework then prior distributions will have to be specified. One option for gathering or at least estimating this information is to employ expert elicitation. Expert elicitation is well studied within statistics and psychology and involves the assessment of the beliefs of a group of experts about an uncertain quantity, (for example an input / parameter within a model), typically in terms of obtaining a probability distribution. One of the challenges in expert elicitation is to minimise the biases that might enter into the judgements made by the individual experts, and then to come to a consensus decision within the group of experts. Effort is made in the elicitation exercise to prevent biases clouding the judgements through well-devised questioning schemes. It is also important that, when reaching a consensus, the experts are exposed to the knowledge of the others in the group. Within the FP7 UncertWeb project (http://www.uncertweb.org/), there is a requirement to build a Webbased tool for expert elicitation. In this paper, we discuss some of the issues of building a Web-based elicitation system - both the technological aspects and the statistical and scientific issues. In particular, we demonstrate two tools: a Web-based system for the elicitation of continuous random variables and a system designed to elicit uncertainty about categorical random variables in the setting of landcover classification uncertainty. The first of these examples is a generic tool developed to elicit uncertainty about univariate continuous random variables. It is designed to be used within an application context and extends the existing SHELF method, adding a web interface and access to metadata. The tool is developed so that it can be readily integrated with environmental models exposed as web services. The second example was developed for the TREES-3 initiative which monitors tropical landcover change through ground-truthing at confluence points. It allows experts to validate the accuracy of automated landcover classifications using site-specific imagery and local knowledge. Experts may provide uncertainty information at various levels: from a general rating of their confidence in a site validation to a numerical ranking of the possible landcover types within a segment. A key challenge in the web based setting is the design of the user interface and the method of interacting between the problem owner and the problem experts. We show the workflow of the elicitation tool, and show how we can represent the final elicited distributions and confusion matrices using UncertML, ready for integration into uncertainty enabled workflows.We also show how the metadata associated with the elicitation exercise is captured and can be referenced from the elicited result, providing crucial lineage information and thus traceability in the decision making process.

Analysis of interactions among variables of renewable energy projects:a case study on renewable energy project in India

This study highlights the variables associated with the implementation of renewable energy (RE) projects for sustainable development in India, by using an interpretive structural modeling (ISM) - based approach to model variables' interactions, which impact RE adoption. These variables have been categorized under enablers that help to enhance implementation of RE projects for sustainable development. A major finding is that public awareness regarding RE for sustainable development is a very significant enabler. For successful implementation of RE projects, it has been observed that top management should focus on improving highdriving power enablers (leadership, strategic planning, public awareness, management commitment, availability of finance, government support, and support from interest groups).

Household waste recycling behavior: a market segmentation model

The potential of social marketing has been recognized in the United Kingdom by the Department for Environment, Food and Rural Affairs (DEFRA) as a useful tool for behavioral change for environmental problems. The techniques of social marketing have been used successfully by health organizations to tackle current public health issues. This article describes a research project which explored the current barriers to recycling household waste and the development of a segmentation model which could be used at the local level by authorities charged with waste collection and disposal. The research makes a unique contribution to social marketing through the introduction of a competencies framework and market segmentation for recycling behaviors.

Project risk management using multiple criteria decision-making technique and decision tree analysis:a case study of Indian oil refinery

This study proposes an integrated analytical framework for effective management of project risks using combined multiple criteria decision-making technique and decision tree analysis. First, a conceptual risk management model was developed through thorough literature review. The model was then applied through action research on a petroleum oil refinery construction project in the Central part of India in order to demonstrate its effectiveness. Oil refinery construction projects are risky because of technical complexity, resource unavailability, involvement of many stakeholders and strict environmental requirements. Although project risk management has been researched extensively, practical and easily adoptable framework is missing. In the proposed framework, risks are identified using cause and effect diagram, analysed using the analytic hierarchy process and responses are developed using the risk map. Additionally, decision tree analysis allows modelling various options for risk response development and optimises selection of risk mitigating strategy. The proposed risk management framework could be easily adopted and applied in any project and integrated with other project management knowledge areas.

Data envelopment analysis model for the appraisal and relative performance evaluation of nurses at an intensive care unit

The appraisal and relative performance evaluation of nurses are very important and beneficial for both nurses and employers in an era of clinical governance, increased accountability and high standards of health care services. They enhance and consolidate the knowledge and practical skills of nurses by identification of training and career development plans as well as improvement in health care quality services, increase in job satisfaction and use of cost-effective resources. In this paper, a data envelopment analysis (DEA) model is proposed for the appraisal and relative performance evaluation of nurses. The model is validated on thirty-two nurses working at an Intensive Care Unit (ICU) at one of the most recognized hospitals in Lebanon. The DEA was able to classify nurses into efficient and inefficient ones. The set of efficient nurses was used to establish an internal best practice benchmark to project career development plans for improving the performance of other inefficient nurses. The DEA result confirmed the ranking of some nurses and highlighted injustice in other cases that were produced by the currently practiced appraisal system. Further, the DEA model is shown to be an effective talent management and motivational tool as it can provide clear managerial plans related to promoting, training and development activities from the perspective of nurses, hence increasing their satisfaction, motivation and acceptance of appraisal results. Due to such features, the model is currently being considered for implementation at ICU. Finally, the ratio of the number DEA units to the number of input/output measures is revisited with new suggested values on its upper and lower limits depending on the type of DEA models and the desired number of efficient units from a managerial perspective.

Changing policies for the automotive industry in an 'old' industrial region:an open innovation model for the UK West Midlands?

Automobile manufacture in the UK West Midlands peaked during the 1950s and early 1960s but, with overseas competition, declined thereafter. Successive policies, such as government supported mergers to form the British Motor Corporation in the 1950s, green-field development away from the region in the 1960s, nationalisation of the (then) British Leyland in the 1970s, Japanese FDI in the 1980s and the Rover-centric Accelerate Project in the 1990s have failed to halt the decline. Since early 2000, regional policy has been the responsibility of the Regional Development Agency, Advantage West Midlands. The RDA has moved away from traditional support based on the needs of big companies or ‘champions’ and adopted an approach centred on a mix of small and large businesses and high level research, and – arguably – an ‘open innovation’ model. Here, we examine these new policies and their potential to create an innovative and competitive regional environment.

Uncertainty analysis in the Model Web

This thesis provides a set of tools for managing uncertainty in Web-based models and workflows.To support the use of these tools, this thesis firstly provides a framework for exposing models through Web services. An introduction to uncertainty management, Web service interfaces,and workflow standards and technologies is given, with a particular focus on the geospatial domain.An existing specification for exposing geospatial models and processes, theWeb Processing Service (WPS), is critically reviewed. A processing service framework is presented as a solutionto usability issues with the WPS standard. The framework implements support for Simple ObjectAccess Protocol (SOAP), Web Service Description Language (WSDL) and JavaScript Object Notation (JSON), allowing models to be consumed by a variety of tools and software. Strategies for communicating with models from Web service interfaces are discussed, demonstrating the difficultly of exposing existing models on the Web. This thesis then reviews existing mechanisms for uncertainty management, with an emphasis on emulator methods for building efficient statistical surrogate models. A tool is developed to solve accessibility issues with such methods, by providing a Web-based user interface and backend to ease the process of building and integrating emulators. These tools, plus the processing service framework, are applied to a real case study as part of the UncertWeb project. The usability of the framework is proved with the implementation of aWeb-based workflow for predicting future crop yields in the UK, also demonstrating the abilities of the tools for emulator building and integration. Future directions for the development of the tools are discussed.

Form follows function:model-driven engineering for clinical trials

We argue that, for certain constrained domains, elaborate model transformation technologies-implemented from scratch in general-purpose programming languages-are unnecessary for model-driven engineering; instead, lightweight configuration of commercial off-the-shelf productivity tools suffices. In particular, in the CancerGrid project, we have been developing model-driven techniques for the generation of software tools to support clinical trials. A domain metamodel captures the community's best practice in trial design. A scientist authors a trial protocol, modelling their trial by instantiating the metamodel; customized software artifacts to support trial execution are generated automatically from the scientist's model. The metamodel is expressed as an XML Schema, in such a way that it can be instantiated by completing a form to generate a conformant XML document. The same process works at a second level for trial execution: among the artifacts generated from the protocol are models of the data to be collected, and the clinician conducting the trial instantiates such models in reporting observations-again by completing a form to create a conformant XML document, representing the data gathered during that observation. Simple standard form management tools are all that is needed. Our approach is applicable to a wide variety of information-modelling domains: not just clinical trials, but also electronic public sector computing, customer relationship management, document workflow, and so on. © 2012 Springer-Verlag.

Managing project risk using combined analytic hierarchy process and risk map

The main purpose of the study is to develop an integrated framework for managing project risks by analyzing risk across project, work package and activity levels, and developing responses. Design/methodology/approach: The study first reviews the literature of various contemporary risk management frameworks in order to identify gaps in project risk management knowledge. Then it develops a conceptual risk management framework using combined analytic hierarchy process (AHP) and risk map for managing project risks. The proposed framework has then been applied to a 1500 km oil pipeline construction project in India in order to demonstrate its effectiveness. The concerned project stakeholders were involved through focus group discussions for applying the proposed risk management framework in the project under study. Findings: The combined AHP and risk map approach is very effective to manage project risks across project, work package and activity levels. The risk factors in project level are caused because of external forces such as business environment (e.g. customers, competitors, technological development, politics, socioeconomic environment). The risk factors in work package and activity levels are operational in nature and created due to internal causes such as lack of material and labor productivity, implementation issues, team ineffectiveness, etc. Practical implications: The suggested model can be applied to any complex project and helps manage risk throughout the project life cycle. Originality/value: Both business and operational risks constitute project risks. In one hand, the conventional project risk management frameworks emphasize on managing business risks and often ignore operational risks. On the other hand, the studies that deal with operational risk often do not link them with business risks. However, they need to be addressed in an integrated way as there are a few risks that affect only the specific level. Hence, this study bridges the gaps. © 2010 Elsevier B.V. All rights reserved.