Ex ante evaluations of alternate data structures for end user queries: Theory and experimental test

The data structure of an information system can significantly impact the ability of end users to efficiently and effectively retrieve the information they need. This research develops a methodology for evaluating, ex ante, the relative desirability of alternative data structures for end user queries. This research theorizes that the data structure that yields the lowest weighted average complexity for a representative sample of information requests is the most desirable data structure for end user queries. The theory was tested in an experiment that compared queries from two different relational database schemas. As theorized, end users querying the data structure associated with the less complex queries performed better Complexity was measured using three different Halstead metrics. Each of the three metrics provided excellent predictions of end user performance. This research supplies strong evidence that organizations can use complexity metrics to evaluate, ex ante, the desirability of alternate data structures. Organizations can use these evaluations to enhance the efficient and effective retrieval of information by creating data structures that minimize end user query complexity.

Managing healthcare quality in project management framework

Healthcare professionals routinely deploy various quality management tools and techniques in order to improve performance of healthcare delivery. However, they are characterised by fragmented approach i.e., they are not linked with the strategic intent of the organisation. This study introduces a holistic quality improvement method, which integrates all quality improvement projects with the strategic intent of the healthcare organisations. It first identifies a healthcare system and its environment. The Strengths, Weaknesses, Opportunities and Threats (SWOT) of the system are then derived with the involvement of the concerned stakeholders. This leads to developing the strategies in order to satisfy customers in line with the organisation's competitive position. These strategies help identify a few projects, the implementation of which ensures achievement of desired quality. The projects are then prioritised with the involvement of the concerned stakeholders and implemented in order to improve the system performance. The effectiveness of the method has been demonstrated using a case study of an intensive care unit at the Eric Williams Medical Sciences Complex Hospital in Trinidad. Copyright © 2007 Inderscience Enterprises Ltd.

Strategy paradigms for the management of quality:dealing with complexity

Quality management is dominated by rational paradigms for the measurement and management of quality, but these paradigms start to “break down”, when faced with the inherent complexity of managing quality in intensely competitive changing environments. In this article, the various theoretical strategy paradigms employed to manage quality are reviewed and the advantages and limitations of these paradigms are highlighted. A major implication of this review is that when faced with complexity, an ideological stance to any single strategy paradigm for the management of quality is ineffective. A case study is used to demonstrate the need for an integrative multi-paradigm approach to the management of quality as complexity increases.

Quality improvement in professional local government services : a longitudinal study

This sustained longitudinal study, carried out in a single local authority, investigates the implementation of a Total Quality Management (TQM) philosophy in professional local government services. At the start of this research, a large majority of what was written about TQM was polemical and based on limited empirical evidence. This thesis seeks to provide a significant and important piece of work, making a considerable contribution to the current state of knowledge in this area. Teams from four professional services within a single local authority participated in this research, providing the main evidence on how the quality management agenda in a local authority can be successfully implemented. To supplement this rich source of data, various other sources and methods of data collection have been used: 1) Interviews were carried out with senior managers from within the authority; 2) Customer focus groups and questionnaires were used; 3) Interviews were carried out with other organisations, all of which were proponents of a TQM philosophy. A number of tools have been developed to assist in gathering data: 1) The CSFs (critical success factors) benchmarking tool; 2) Five Stages of Quality Improvement Model. A Best Practice Quality Improvement Model, arising from an analysis of the literature and the researcher's own experience is proposed and tested. From the results a number of significant conclusions have been drawn relating to: 1) Triggers for change; 2) Resistance of local government professionals to change 3) Critical success factors and barriers to quality improvement in professional local government services; 4) The problems associated with participant observation and other methodological issues used.

Designing a safety management support system using open architecture databases: the requirements of information representation in the support of managers' risk-related decision-making

This research was conducted at the Space Research and Technology Centre o the European Space Agency at Noordvijk in the Netherlands. ESA is an international organisation that brings together a range of scientists, engineers and managers from 14 European member states. The motivation for the work was to enable decision-makers, in a culturally and technologically diverse organisation, to share information for the purpose of making decisions that are well informed about the risk-related aspects of the situations they seek to address. The research examined the use of decision support system DSS) technology to facilitate decision-making of this type. This involved identifying the technology available and its application to risk management. Decision-making is a complex activity that does not lend itself to exact measurement or precise understanding at a detailed level. In view of this, a prototype DSS was developed through which to understand the practical issues to be accommodated and to evaluate alternative approaches to supporting decision-making of this type. The problem of measuring the effect upon the quality of decisions has been approached through expert evaluation of the software developed. The practical orientation of this work was informed by a review of the relevant literature in decision-making, risk management, decision support and information technology. Communication and information technology unite the major the,es of this work. This allows correlation of the interests of the research with European public policy. The principles of communication were also considered in the topic of information visualisation - this emerging technology exploits flexible modes of human computer interaction (HCI) to improve the cognition of complex data. Risk management is itself an area characterised by complexity and risk visualisation is advocated for application in this field of endeavour. The thesis provides recommendations for future work in the fields of decision=making, DSS technology and risk management.

The interaction between the implementation of an occupational health and safety management system and safety culture:a case study in the rubber industry

A prominent theme emerging in Occupational Health and Safety (OSH) is the development of management systems. A range of interventions, according to a prescribed route detailed by one of the management systems, can be introduced into an organisation with some expectation of improved OSH performance. This thesis attempts to identify the key influencing factors that may impact upon the process of introducing interventions, (according to B88800: 1996, Guide to Implementing Occupational Health and Safety Management Systems) into an organisation. To help identify these influencing factors a review of possible models from the sphere of Total Quality Management (TQM) was undertaken and the most suitable TQM model selected for development and use in aSH. By anchoring the aSH model's development in the reviewed literature a range ofeare, medium and low level influencing factors were identified. This model was developed in conjunction with the research data generated within the case study organisation (rubber manufacturer) and applied to the organisation. The key finding was that the implementation of an OSH intervention was dependant upon three broad vectors of influence. These are the Incentive to introduce change within an organisation which refers to the drivers or motivators for OSH. Secondly the Ability within the management team to actually implement the changes refers to aspects, amongst others, such as leadership, commitment and perceptions of OSH. Ability is in turn itself influenced by the environment within which change is being introduced. TItis aspect of Receptivity refers to the history of the plant and characteristics of the workforce. Aspects within Receptivity include workforce profile and organisational policies amongst others. It was found that the TQM model selected and developed for an OSH management system intervention did explain the core influencing factors and their impact upon OSH performance. It was found that within the organisation the results that may have been expected from implementation of BS8800:1996 were not realised. The OSH model highlighted that given the organisation's starting point, a poor appreciation of the human factors of OSH, gave little reward for implementation of an OSH management system. In addition it was found that general organisational culture can effectively suffocate any attempts to generate a proactive safety culture.

Introduction : the role of quality, production and technological innovation in improving competitive performance

Quality, production and technological innovation management rank among the most important matters of concern to modern manufacturing organisations. They can provide companies with the decisive means of gaining a competitive advantage, especially within industries where there is an increasing similarity in product design and manufacturing processes. The papers in this special issue of International Journal of Technology Management have all been selected as examples of how aspects of quality, production and technological innovation can help to improve competitive performance. Most are based on presentations made at the UK Operations Management Association's Sixth International Conference held at Aston University at which the theme was 'Getting Ahead Through Technology and People'. At the conference itself over 80 papers were presented by authors from 15 countries around the world. Among the many topics addressed within the conference theme, technological innovation, quality and production management emerged as attracting the greatest concern and interest of delegates, particularly those from industry. For any new initiative to be implemented successfully, it should be led from the top of the organization. Achieving the desired level of commitment from top management can, however, be a difficulty. In the first paper of this issue, Mackness investigates this question by explaining how systems thinking can help. In the systems approach, properties such as 'emergence', 'hierarchy', 'commnication' and 'control' are used to assist top managers in preparing for change. Mackness's paper is then complemented by Iijima and Hasegawa's contribution in which they investigate the development of Quality Information Management (QIM) in Japan. They present the idea of a Design Review and demonstrate how it can be used to trace and reduce quality-related losses. The next paper on the subject of quality is by Whittle and colleagues. It relates to total quality and the process of culture change within organisations. Using the findings of investigations carried out in a number of case study companies, they describe four generic models which have been identified as characterising methods of implementing total quality within existing organisation cultures. Boaden and Dale's paper also relates to the management of quality, but looks specifically at the construction industry where it has been found there is still some confusion over the role of Quality Assurance (QA) and Total Quality Management (TQM). They describe the results of a questionnaire survey of forty companies in the industry and compare them to similar work carried out in other industries. Szakonyi's contribution then completes this group of papers which all relate specifically to the question of quality. His concern is with the two ways in which R&D or engineering managers can work on improving quality. The first is by improving it in the laboratory, while the second is by working with other functions to improve quality in the company. The next group of papers in this issue all address aspects of production management. Umeda's paper proposes a new manufacturing-oriented simulation package for production management which provides important information for both design and operation of manufacturing systems. A simulation for production strategy in a Computer Integrated Manufacturing (CIM) environment is also discussed. This paper is then followed by a contribution by Tanaka and colleagues in which they consider loading schedules for manufacturing orders in a Material Requirements Planning (MRP) environment. They compare mathematical programming with a knowledge-based approach, and comment on their relative effectiveness for different practical situations. Engstrom and Medbo's paper then looks at a particular aspect of production system design, namely the question of devising group working arrangements for assembly with new product structures. Using the case of a Swedish vehicle assembly plant where long cycle assembly work has been adopted, they advocate the use of a generally applicable product structure which can be adapted to suit individual local conditions. In the last paper of this particular group, Tay considers how automation has affected the production efficiency in Singapore. Using data from ten major industries he identifies several factors which are positively correlated with efficiency, with capital intensity being of greatest interest to policy makers. The two following papers examine the case of electronic data interchange (EDI) as a means of improving the efficiency and quality of trading relationships. Banerjee and Banerjee consider a particular approach to material provisioning for production systems using orderless inventory replenishment. Using the example of a single supplier and multiple buyers they develop an analytical model which is applicable for the exchange of information between trading partners using EDI. They conclude that EDI-based inventory control can be attractive from economic as well as other standpoints and that the approach is consistent with and can be instrumental in moving towards just-in-time (JIT) inventory management. Slacker's complementary viewpoint on EDI is from the perspective of the quality relation-ship between the customer and supplier. Based on the experience of Lucas, a supplier within the automotive industry, he concludes that both banks and trading companies must take responsibility for the development of payment mechanisms which satisfy the requirements of quality trading. The three final papers of this issue relate to technological innovation and are all country based. Berman and Khalil report on a survey of US technological effectiveness in the global economy. The importance of education is supported in their conclusions, although it remains unclear to what extent the US government can play a wider role in promoting technological innovation and new industries. The role of technology in national development is taken up by Martinsons and Valdemars who examine the case of the former Soviet Union. The failure to successfully infuse technology into Soviet enterprises is seen as a factor in that country's demise, and it is anticipated that the newly liberalised economies will be able to encourage greater technological creativity. This point is then taken up in Perminov's concluding paper which looks in detail at Russia. Here a similar analysis is made of the concluding paper which looks in detail at Russia. Here a similar analysis is made of the Soviet Union's technological decline, but a development strategy is also presented within the context of the change from a centralised to a free market economy. The papers included in this special issue of the International Journal of Technology Management each represent a unique and particular contribution to their own specific area of concern. Together, however, they also argue or demonstrate the general improvements in competitive performance that can be achieved through the application of modern principles and practice to the management of quality, production and technological innovation.

Visualisation of quality information for geospatial and remote sensing data:providing the GIS community with the decision support tools for geospatial dataset quality evaluation

The evaluation of geospatial data quality and trustworthiness presents a major challenge to geospatial data users when making a dataset selection decision. The research presented here therefore focused on defining and developing a GEO label – a decision support mechanism to assist data users in efficient and effective geospatial dataset selection on the basis of quality, trustworthiness and fitness for use. This thesis thus presents six phases of research and development conducted to: (a) identify the informational aspects upon which users rely when assessing geospatial dataset quality and trustworthiness; (2) elicit initial user views on the GEO label role in supporting dataset comparison and selection; (3) evaluate prototype label visualisations; (4) develop a Web service to support GEO label generation; (5) develop a prototype GEO label-based dataset discovery and intercomparison decision support tool; and (6) evaluate the prototype tool in a controlled human-subject study. The results of the studies revealed, and subsequently confirmed, eight geospatial data informational aspects that were considered important by users when evaluating geospatial dataset quality and trustworthiness, namely: producer information, producer comments, lineage information, compliance with standards, quantitative quality information, user feedback, expert reviews, and citations information. Following an iterative user-centred design (UCD) approach, it was established that the GEO label should visually summarise availability and allow interrogation of these key informational aspects. A Web service was developed to support generation of dynamic GEO label representations and integrated into a number of real-world GIS applications. The service was also utilised in the development of the GEO LINC tool – a GEO label-based dataset discovery and intercomparison decision support tool. The results of the final evaluation study indicated that (a) the GEO label effectively communicates the availability of dataset quality and trustworthiness information and (b) GEO LINC successfully facilitates ‘at a glance’ dataset intercomparison and fitness for purpose-based dataset selection.

Rubric-Q:adding quality-related elements to the GEOSS clearinghouse datasets

Geospatial data have become a crucial input for the scientific community for understanding the environment and developing environmental management policies. The Global Earth Observation System of Systems (GEOSS) Clearinghouse is a catalogue and search engine that provides access to the Earth Observation metadata. However, metadata are often not easily understood by users, especially when presented in ISO XML encoding. Data quality included in the metadata is basic for users to select datasets suitable for them. This work aims to help users to understand the quality information held in metadata records and to provide the results to geospatial users in an understandable and comparable way. Thus, we have developed an enhanced tool (Rubric-Q) for visually assessing the metadata quality information and quantifying the degree of metadata population. Rubric-Q is an extension of a previous NOAA Rubric tool used as a metadata training and improvement instrument. The paper also presents a thorough assessment of the quality information by applying the Rubric-Q to all dataset metadata records available in the GEOSS Clearinghouse. The results reveal that just 8.7% of the datasets have some quality element described in the metadata, 63.4% have some lineage element documented, and merely 1.2% has some usage element described. © 2013 IEEE.

Teaching Statistics to Engineers: Learning from Experiential Data

The purpose of the work is to claim that engineers can be motivated to study statistical concepts by using the applications in their experience connected with Statistical ideas. The main idea is to choose a data from the manufacturing factility (for example, output from CMM machine) and explain that even if the parts used do not meet exact specifications they are used in production. By graphing the data one can show that the error is random but follows a distribution, that is, there is regularily in the data in statistical sense. As the error distribution is continuous, we advocate that the concept of randomness be introducted starting with continuous random variables with probabilities connected with areas under the density. The discrete random variables are then introduced in terms of decision connected with size of the errors before generalizing to abstract concept of probability. Using software, they can then be motivated to study statistical analysis of the data they encounter and the use of this analysis to make engineering and management decisions.

Improving resource management in virtualized data centers using application performance models

The rapid growth of virtualized data centers and cloud hosting services is making the management of physical resources such as CPU, memory, and I/O bandwidth in data center servers increasingly important. Server management now involves dealing with multiple dissimilar applications with varying Service-Level-Agreements (SLAs) and multiple resource dimensions. The multiplicity and diversity of resources and applications are rendering administrative tasks more complex and challenging. This thesis aimed to develop a framework and techniques that would help substantially reduce data center management complexity.^ We specifically addressed two crucial data center operations. First, we precisely estimated capacity requirements of client virtual machines (VMs) while renting server space in cloud environment. Second, we proposed a systematic process to efficiently allocate physical resources to hosted VMs in a data center. To realize these dual objectives, accurately capturing the effects of resource allocations on application performance is vital. The benefits of accurate application performance modeling are multifold. Cloud users can size their VMs appropriately and pay only for the resources that they need; service providers can also offer a new charging model based on the VMs performance instead of their configured sizes. As a result, clients will pay exactly for the performance they are actually experiencing; on the other hand, administrators will be able to maximize their total revenue by utilizing application performance models and SLAs. ^ This thesis made the following contributions. First, we identified resource control parameters crucial for distributing physical resources and characterizing contention for virtualized applications in a shared hosting environment. Second, we explored several modeling techniques and confirmed the suitability of two machine learning tools, Artificial Neural Network and Support Vector Machine, to accurately model the performance of virtualized applications. Moreover, we suggested and evaluated modeling optimizations necessary to improve prediction accuracy when using these modeling tools. Third, we presented an approach to optimal VM sizing by employing the performance models we created. Finally, we proposed a revenue-driven resource allocation algorithm which maximizes the SLA-generated revenue for a data center.^

Information systems to support decision-making in *construction owner organizations: A data warehousing approach

Construction organizations typically deal with large volumes of project data containing valuable information. It is found that these organizations do not use these data effectively for planning and decision-making. There are two reasons. First, the information systems in construction organizations are designed to support day-to-day construction operations. The data stored in these systems are often non-validated, non-integrated and are available in a format that makes it difficult for decision makers to use in order to make timely decisions. Second, the organizational structure and the IT infrastructure are often not compatible with the information systems thereby resulting in higher operational costs and lower productivity. These two issues have been investigated in this research with the objective of developing systems that are structured for effective decision-making. ^ A framework was developed to guide storage and retrieval of validated and integrated data for timely decision-making and to enable construction organizations to redesign their organizational structure and IT infrastructure matched with information system capabilities. The research was focused on construction owner organizations that were continuously involved in multiple construction projects. Action research and Data warehousing techniques were used to develop the framework. ^ One hundred and sixty-three construction owner organizations were surveyed in order to assess their data needs, data management practices and extent of use of information systems in planning and decision-making. For in-depth analysis, Miami-Dade Transit (MDT) was selected which is in-charge of all transportation-related construction projects in the Miami-Dade county. A functional model and a prototype system were developed to test the framework. The results revealed significant improvements in data management and decision-support operations that were examined through various qualitative (ease in data access, data quality, response time, productivity improvement, etc.) and quantitative (time savings and operational cost savings) measures. The research results were first validated by MDT and then by a representative group of twenty construction owner organizations involved in various types of construction projects. ^

Information systems to support decision-making in construction owner organizations : a data warehousing approach

Construction organizations typically deal with large volumes of project data containing valuable information. It is found that these organizations do not use these data effectively for planning and decision-making. There are two reasons. First, the information systems in construction organizations are designed to support day-to-day construction operations. The data stored in these systems are often non-validated, nonintegrated and are available in a format that makes it difficult for decision makers to use in order to make timely decisions. Second, the organizational structure and the IT infrastructure are often not compatible with the information systems thereby resulting in higher operational costs and lower productivity. These two issues have been investigated in this research with the objective of developing systems that are structured for effective decision-making. A framework was developed to guide storage and retrieval of validated and integrated data for timely decision-making and to enable construction organizations to redesign their organizational structure and IT infrastructure matched with information system capabilities. The research was focused on construction owner organizations that were continuously involved in multiple construction projects. Action research and Data warehousing techniques were used to develop the framework. One hundred and sixty-three construction owner organizations were surveyed in order to assess their data needs, data management practices and extent of use of information systems in planning and decision-making. For in-depth analysis, Miami-Dade Transit (MDT) was selected which is in-charge of all transportation-related construction projects in the Miami-Dade county. A functional model and a prototype system were developed to test the framework. The results revealed significant improvements in data management and decision-support operations that were examined through various qualitative (ease in data access, data quality, response time, productivity improvement, etc.) and quantitative (time savings and operational cost savings) measures. The research results were first validated by MDT and then by a representative group of twenty construction owner organizations involved in various types of construction projects.

Management technologies - are they worth it? A normative study of ISO 9001 and project management

This research inquires into the value of two common ‘management technologies’, namely ISO 9001 and project management. To avoid certain methodological problems, we study the value of these micro-level practices by inductively analysing macro-level data, specifically the intensity of project management and ISO 9001 certification (termed project management score and ISO 9001 score) in different countries against national measures of wealth and innovation. There is no correlation between ISO 9001 score and innovation, while high ISO 9001 scores are correlated with decreasing levels of wealth. The project management score is positively correlated with wealth and with innovation, though very high project management scores are negatively correlated with innovation. The study includes a cluster analysis which finds that, with one exception, countries tend to adopt either project management or ISO 9001 but not both. The analysis indicates that project management is more likely to be associated with high innovation and high wealth than ISO 9001.

A novel near real-time quality-control procedure for radiometric profiles measured by Bio-Argo floats: protocols and performances

An array of Bio-Argo floats equipped with radiometric sensors has been recently deployed in various open ocean areas representative of the diversity of trophic and bio-optical conditions prevailing in the so-called Case 1 waters. Around solar noon and almost everyday, each float acquires 0-250 m vertical profiles of Photosynthetically Available Radiation and downward irradiance at three wavelengths (380, 412 and 490 nm). Up until now, more than 6500 profiles for each radiometric channel have been acquired. As these radiometric data are collected out of operator’s control and regardless of meteorological conditions, specific and automatic data processing protocols have to be developed. Here, we present a data quality-control procedure aimed at verifying profile shapes and providing near real-time data distribution. This procedure is specifically developed to: 1) identify main issues of measurements (i.e. dark signal, atmospheric clouds, spikes and wave-focusing occurrences); 2) validate the final data with a hierarchy of tests to ensure a scientific utilization. The procedure, adapted to each of the four radiometric channels, is designed to flag each profile in a way compliant with the data management procedure used by the Argo program. Main perturbations in the light field are identified by the new protocols with good performances over the whole dataset. This highlights its potential applicability at the global scale. Finally, the comparison with modeled surface irradiances allows assessing the accuracy of quality-controlled measured irradiance values and identifying any possible evolution over the float lifetime due to biofouling and instrumental drift.