Signal Replacement decisions are often made based on the experience of the Traffic Engineers. These decisions are made while considering the deployment time of the system, the new technology available, and the performance of the system in the given location. However, there is no set of proper guidelines or methods which can quantify the system replacement decision in large scale projects. This thesis presents a methodology that can be applied to determine optimal migration plans for traffic signal controllers. A Multi-Criteria Decision Making technique has been adopted to evaluate various traffic signal controllers. Various controller manuals were studied and information was obtained from the vendors of the controllers. In addition to that, Geographic Information System (GIS) has been used as a tool to evaluate and identify the areas where the traffic signal controllers have to be replaced first. The study considers the budget constraints and the benefits that can be obtained by the replacement of the controllers. This thesis presents the Methodology adopted for the Migration Plan and a case study implementation on the Northern Virginia Region. Finally it presents the conclusions drawn from the research with insights into the scope for further research. / Master of Science

New Zealand faces a range of food safety hazards. Microbial hazards alone were estimated to cause over 2,000 years of lost healthy life in 2011 (Cressey, 2012) and $62m in medical costs and lost productivity in 2009 (Gadiel & Abelson, 2010). Chemical hazards are thought to be well managed through existing controls (Vannoort & Thomson, 2009) whereas microbial hazards are considered harder to control, primarily due to their ability to reproduce along the food production chain. Microbial hazards are thought to cause the majority of acute foodborne gastroenteritis. This research reviewed food safety literature and official documentation, and conducted 55 interviews, mostly with food safety experts from different stakeholder groups, to examine the food safety decision-making environment in New Zealand. This research explores the concept of the ‘stakeholder’ in the context of food safety decision-making and proposes an inclusive ‘stakeholder’ definition as any group which is able to affect, or be affected by, the decision-making process. Utilising this definition, and guided by interviews, New Zealand stakeholders in food safety decision-making were identified and classified as follows: •Regulators •Public health authorities •Food safety scientists/academics •Consumers •Māori •Food Businesses (further classified as): o Farmers o Processors o Food retailers o Exporters Interviews with stakeholders from these groups highlighted twelve criteria as being relevant to multiple groups during food safety intervention evaluation: •Effectiveness •Financial cost •Market Access •Consumer Perceptions •Ease of Implementation •Quality or Suitability •Quality of Science •Equity of Costs •Equity of Benefits •Workplace Safety •Cultural Impact •Animal Welfare There are a number of different ways to measure or assess performance on these criteria. Some are able to be quantitatively measured, while others may require the use of value judgements. This thesis used the Disability-Adjusted Life Year (DALY) metric for quantifying effectiveness during the testing of different MCDA models. This thesis reviews the MCDA process and the food safety specific MCDA literature. There are different ways of conducting MCDA. In particular, there are a large number of models available for the aggregation phase; the process of converting model inputs, in the form of criteria scores and weights, into model recommendations. This thesis has described and reviewed the main classes of model. The literature review and interview process guided the construction and testing of three classes of MCDA model; the Weighted Sum, Analytic Hierarchy Process (AHP) and PROMETHEE models. These models were selected due to their having different characteristics and degrees of complexity, as well as their popularity in the food safety and Health Technology Assessment (HTA) literature. Models were tested on the problem of selecting the most appropriate intervention to address the historic Campylobacter in poultry problem in New Zealand during the mid-2000s. Experimentation was conducted on these models to explore how different configurations utilise data and produce model outputs. This experimentation included: •Varying the format of input data •Exploring the effects of including/excluding criteria •Methods for sensitivity analysis •Exploring how data inputs and outputs can be elicited and presented using visual tools • Creating and using hybrid MCDA models The results of this testing are a key output of this thesis and provide insight into how such models might be used in food safety decision-making. The conclusions reached throughout this research phase can be classified into one of two broad groups: •Those relating to MCDA as a holistic process/methodology for decision-making •Those relating to the specific models and mathematical procedures for generating numerical inputs and outputs This thesis demonstrates that food-safety decision-making is a true multi-criteria, multi-stakeholder problem. The different stakeholders in food-safety decision-making do not always agree on the value and importance of the attributes used to evaluate competing intervention schemes. MCDA is well suited to cope with such complexity as it provides a structured methodology for the systematic and explicit identification, recording and aggregation of qualitative and quantitative information, gathered from a number of different sources, with the output able to serve as a basis for decision-making. The MCDA models studied in this thesis range from models that are simple and quick to construct and use, to more time consuming models with sophisticated algorithms. The type of model used for MCDA, the way these models are configured and the way inputs are generated or elicited can have a significant impact on the results of an analysis. This thesis has identified a number of key methodological considerations for those looking to employ one of the many available MCDA models. These considerations include: •Whether a model can accommodate the type and format of input data •The desired degree of compensation between criteria (i.e. full, partial or no compensation) •Whether the goal of an analysis is the identification of a ‘best’ option(s), or the facilitation of discussion, and communication of data •The degree of transparency required from a model and whether an easily understood audit trail is desired/required •The desired output of a model (e.g. complete or partial ranking). This thesis has also identified a number of practical considerations when selecting which model to use in food safety decision-making. These include: •The amount of time and energy required of stakeholders in the generation of data inputs (elicitation burden) •The degree of training required for participants •How data inputs are to be elicited and aggregated in different group decision-making environments •The availability of MCDA software for assisting an analysis Considering the above points will assist users in selecting a suitable MCDA model that meets their requirements and constraints. This thesis provides original and practical knowledge to assist groups or individuals looking to employ MCDA in the context of food-safety intervention decision-making. This research could also serve as a guide for those looking to evaluate a different selection of MCDA models.

The aim of this diploma thesis is to devise general evaluation procedure of current accounts for associations and then to compare the theoretical results with the results of the questionnaire survey. The aim of the questionnaire survey is to find out what accounts the associations use and why. The theoretical part of this thesis is focused on the scientific discipline called multi-criteria decision making, its basic terminology, the methods of setting the criterions' weights and selected multi-criteria decision making methods. Finally, the associations are described according to valid legislation. In the practical part, selected accounts for specific clients are evaluated by using three multi-criteria decision making methods and the questionnaire survey is evaluated too. The conclusion is dedicated a comparison of the theoretical evaluation results with the questionnaire survey results and the author's own view of this issue. Familiarization of the author with the associations' activities during a personal meeting with them is the main benefit of this thesis for the author. The finding that the accounts of some of them are not as advantageous as they were before is the benefit for the associations. Some of them decided to visit their bank and change the account to the account recommended by the author.

The current decision-making processes involved in Environmental Impact Assessments (EIAs) in South Africa suffer from a lack of coherence and do not include evaluation of trade-offs between qualitative and quantitative impacts, as well as environmental, economic, and social dimensions. In addition, insufficient capacity and knowledge among authorities, a lack of objectivity among Environmental Assessment Practitioners (EAPs), and mediocre reports add to the problems associated with effective decision-making. This work presents a framework aimed at improving the effectiveness and objectivity of the decision-making process applied in South Africa’s EIAs in the energy sector. A number of decision-making models and tools are available to researchers and practitioners throughout the world that could potentially be applied in EIAs. Among these are Cost-Benefit Analysis (CBA), Rapid Impact Assessment Matrix (RIAM), and Multi Criteria Analysis (MCA). Each of the tools has its own advantages and disadvantages. With respect to the CBA, its biggest disadvantage is the fact that it requires conversion into monetary terms of all impacts, which is sometimes difficult to achieve. The RIAM, on the other hand, fails to provide a systematic approach to the ranking of alternatives. Both of these issues are addressed by the MCA tools. The MCA framework, furthermore, is universal, transparent, easy to replicate, and does not require a particularly large amount of labour and financial resources to complete. It is, however, subjective, but this shortcoming can be overcome by making the decision process more transparent. The framework proposed in this research paper is based on the Multi Criteria Analysis (MCA) technique that allows the identification of the proposed development's cumulative impact versus the current status of the environment. It then compares possible alternatives, where available, in order to identify the most optimal solution. The proposed solution takes into account the trade-offs between the different impact metrics. The research methodology followed in this paper comprised four steps, namely:<ul><li> Selection of case studies, </li><li> Information collection, </li><li> Framework application and testing and </li><li> Feedback. </li></ul> The development of the framework followed an eight-step approach that is generic for MCA and was tested on two case studies that have already gone through the Environmental Impact Assessment process, i.e. the Open Cycle Gas Turbine (OCGT) plant in the Western Cape and the Concentrating Solar Power (CSP) plant in the Northern Cape. The former was evaluated against the "no-go option", but included a decision tree comprised of impact areas, categories of impacts and dimensions (environmental, social, and economic). The latter included alternatives for four components of the project, but the decision tree comprised only of categories and dimensions. The effectiveness of the framework was verified by testing the results of the case studies against the recommendations proposed in the respective Environmental Impact Reports. In all cases, but one, the results of the framework correlated with the recommendations made by the Environmental Assessment Practitioners in the respective studies. In addition, a workshop with the decision-makers was held to obtain their viewpoints regarding the usefulness of the framework in their decision-making environment. These decision-makers supported the use of the framework in their environment as it offered an integrated and transparent approach to the evaluation of projects and alternatives. They emphasised, however, that the decision-making process was complex and the application of the framework alone would not be able to address all the challenges. The case studies demonstrated that the proposed framework could be successfully applied in the process of undertaking impact assessments in the energy sector. It can be used to determine the trade-offs between impacts and dimensions, while taking into consideration the opinions of specialists and decision-makers when assigning weights. The framework has the ability to clearly illustrate the benefit of introducing mitigation measures and it also indicates an alternative that produces the optimal cumulative impact. In conclusion, the work presented contributes to the new body of knowledge in the field of Environmental Impact Assessment in the energy sector as it will assist authorities in making objective and informed decisions, while ensuring greater transparency in the process. It also opens opportunities for conducting follow-on investigations, such the application of the framework in other sectors of the economy, undertaking a sensitivity analysis to compare the range of scores used in the evaluation of impacts, and investigating the possibility of acquiring input from Interested and Affected Parties (I&APs) and integrating those into the framework. / Dissertation (MSc)--University of Pretoria, 2011. / Graduate School of Technology Management (GSTM) / unrestricted

The increasing global deficit of healthcare resources makes efficiency improvements in the healthcare industry a complete necessity to assure safe and available healthcare for everyone. Digitalization is expected to play a fundamental role in this transition and digital primary healthcare providers have in recent years developed into a substantial part of the Swedishprimary care sector. Several of those have built solutions for automated triage, where the role of a triage officer in traditional primary care is replaced by an automated process, in which an triage algorithm directly refers the patient to the appropriate level of care. Despite the rise of digital healthcare providers and automated primary care triage systems in particular, research on the implications of automating the triage process in primary healthcare is scarce. This study aims to assess the potential of using MCDM models for automated triage in digital primary care, by conducting a single case study at one of the leading digital healthcare providers. The study is separated into two phases. In phase one, interviews are conducted to qualitatively determine what set of factors to include in an automated MCDM triage model.In phase two, the resulting model is simulated to evaluate the performance compared to the traditional triage model in which all patient journeys start with an initial nurse meeting. The study shows that an automated MCDM triage model can improve cost efficiency in terms of clinician salary costs and productivity in terms of fewer consultations per patient, compared to the traditional triage model. However, the traditional triage model is shown to be more efficient in terms of only utilizing doctor resources for patients in absolute need of doctor care. / Det ökande underskottet av sjukvårdsresurser gör effektivitetsförbättringar i sjukvårdsbranschen nödvändigt för att säkerställa säker och tillgänglig sjukvård för alla. Digitalisering förväntas fylla en fundamental roll i denna transformation och digitala vårdgivare i primärvården har under de senaste åren växt till en betydande del av den svenska primärvårdssektorn. Flertalet av dessa har byggt lösningar för automatiserat triage, där triagefunktionärens roll ersätts av en automatiserad process där en triagealgoritm direkt hänvisar patienten till den lämpliga vårdnivån. Trots tillväxten av digitala vårdgivare i primärvården och deras automatiserade triagesystem i primärvården är forskning kring effekterna av att automatisera triageprocessen i primärvården begränsad. Denna studie strävar efter att utvärdera potentialen i att använda MCDM-modeller för automatiserat triage i den digitala primärvården genom en casestudie på en av de ledande digitala vårdgivarna i primärvården. Studien är uppdelad i två delar. I del ett genomförs intervjuer för att kvalitativt fastställa vilka faktorer som bör inkluderas i en automatiserad MCDM-modell för triage. I del två simuleras den resulterande MCDM-modellen för att utvärdera dess resultat jämfört med den traditionella triagemodellen i vilken alla patienter har ett inledande möte med en sjuksköterska. Studien visar att en automatiserad MCDM-modell för triage kan förbättra kostnadseffektiviteten i termer av lönekostnader och produktivitet i termer av färre konsultationer per patient, jämfört med den traditionella triagemodellen. Däremot visar den traditionella triagemodellen högre effektivitet i termer av att enbart utnyttja läkarresurser för patienter i absolut behov av läkarvård.

<p dir="ltr">Highway safety continues to pose a serious challenge to the social sustainability of transportation systems, and initiatives are being pursued at all levels of government to reduce the high fatality count of 42,000. At the same time, it is sought to ensure higher travel efficiency in order to increase economic productivity. The emergence of automated transportation provides great promise to mitigate these ills of the transportation sector that have persisted for so many decades. With regards to safety, such promise is rooted in the capability of autonomous vehicles to self-drive some or all of the time, thus reducing the impact of inherently errant human driving to which 95% of all crashes have been attributed. With regards to mobility, such promise is guided by the capability of the autonomous vehicle to carry out path planning, navigation, and vehicle controls in ways that are far more efficient than the human brain, thereby facilitating mobility and reducing congestion-related issues such as delay, emissions, driver frustration, and so on.</p><p dir="ltr">Unfortunately, the two key outcomes (safety and mobility) are reciprocal in the sense that navigation solutions that enhance safety generally tend to reduce mobility, and vice versa. As such, there is a need to assign values explicit to these performance criteria in order to develop balanced solutions for AV decisions. Most existing machine-learning-based path planning algorithms derive these weights using a learning approach. Unfortunately, the stability of these weights across time, individuals, and trip types, is not guaranteed. It is necessary to develop weights and processes that are trip situation-specific. Secondly, user trust in automation remains a key issue, given the relatively recent emergence of this technology and a few highly-publicized crashes, which has led to reservations among potential users.</p><p dir="ltr">To address these research questions, this thesis identifies various situational contexts of the problem, identifies the alternatives (the viable trajectories by fitting curves between the vehicle maneuver’s initial and final positions), develops the decision criteria (safety, mobility, comfort), carries out weighting of the criteria to reflect their relative significance, and scales the criteria to develop dimensionless equivalents of their raw values. Finally, a process for amalgamating the overall impacts of each driving decision alternative is developed based on the weighted and scaled criteria, to identify the best decision (optimal trajectory path). This multi-criteria decision making (MCDM) problem involves the collection of data through questionnaire surveys.</p><p dir="ltr">The weights obtained early in the MCDM process could be integrated into any one of two types of planning algorithms. First, they could be incorporated into interpolating curve-based planning algorithms, to identify the optimal trajectory based on human preferences. Additionally, they can be integrated into optimization-based planning algorithms to allocate weights to the various functions used.</p><p dir="ltr">Overall, this research aims to align the behavior of autonomous vehicles closely with human-driven vehicles, serving two primary purposes: first, facilitating their seamless coexistence on mixed-traffic roads and second, enhancing public acceptance of autonomous vehicles.</p>

The approach to water management worldwide is currently in transition, with a shift from centralised infrastructures to greater consideration of decentralised technologies, such as rainwater harvesting (RWH). Initiated by recognition of drivers, including water demand, increasing risk of ground-water pollution and flooding, the value of RWH is filtering across the academic-policy boundary. However, in Nigeria, implementation of sustainable water management (SWM), such as RWH systems, is inefficient social, environmental and technical barriers, concerns and knowledge gaps exist, which currently restrict its widespread utilisation. This inefficiency contributes to water scarcity, water-borne diseases, and loss of lives and property due to flooding. Meanwhile, several RWH technologies have been developed to improve SWM through both demand and storm-water management. Such technologies involve the use of storage tanks, surface water reservoirs and ground-water recharge pits as storage systems. A framework was developed to assess the significance and extent of water management problems, match the problems with existing RWH-based solutions and develop a robust ready-to-use multi-criteria analysis tool that can quantify the costs and benefits of implementing several RWH-based storage systems. The methodology adopted was the mixed method approach, involving a detailed literature review, followed by a questionnaire survey of 1067 household respondents, 135 Nigerian Architects and Civil Engineers and focus group discussion with Stakeholders. A total of 1042 sets of data were collected through a questionnaire survey and analysed using SPSS, Excel and selected statistical methods to derive weightings of the attributes for the tool. Following this, three case studies were selected to collect data for hydrological modelling using the RainCycle model. From the results it is found that the most important barrier constraining sustainable RWH regime in Ibadan was obsolete and insufficient operational equipment, followed by poor renumeration of water corporation staff and misuse of available funds. In addition, the measure of importance of storage capacity was established, with the highest score of 4.5 which reflects the general inadequacy of storage as a major barrier to the adoption of RWH as a sustainable water management method. Further, respondents’ major health hazards associated with drinking contaminated water was established. A larger proportion (61.2%) of respondents chose prevalence of typhoid fever; some have a prevalence of diarrhea (19.4%), while few of respondents’ water sources is free from water-borne diseases (2.3%). The tool developed is an integrated platform of related evaluation techniques, including Whole Life Cycle Cost Analysis and Multi-Attribute Utility Theory. The tool uses data including cost and quantities of materials for building a RWH storage system and quantifies the cost and benefits of alternative RWH-based systems that can improve project management. This tool is novel, given its integration of the analytical techniques mentioned above and application for selecting the most appropriate RWH-based SWM systems. The implementation of the tool is envisaged to provide an objective platform for the quantification of the costs and benefits of RWH-based systems prior to implementation.

Kuwait’s per capita electrical energy consumption is among the largest in the world, reaching 13,663 kWh per person in 2011. The electricity demand in Kuwait is increasing, which requires additional investments in power generation. A particular challenge in Kuwait is the peak demand in summer, when extreme heat increases air conditioning loads. Peak demand reached 11,220 MW in 2011, with a fast growth rate averaging 5.6% over the last decade and a maximum production capacity of around 14,720 MW. It is not possible to cope with this demand simply by increasing generation capacity. Therefore, the only alternative available to Kuwait is to control electricity demand via demand-side management. The main objective of this research is to assess and select the optimal demand- side management (DSM) technologies for buildings in the governmental sector (office, religious and school buildings) and to investigate the key factors in the evaluation process. To achieve the research objective, a model was proposed using multi-criteria decision-making techniques to enable the forecasting and comparison of DSM alternatives that are suitable for buildings. The developed model includes environmental, economic, technical and social considerations. The research methodology is based on three main phases. Phase 1: Data collection through a mail questionnaire that was sent to 42 experts for the identification of criteria and demand-side management alternatives. Phase 2: Screening and narrowing of the data collected in Phase 1 using a set of questionnaires, including the identification of potential DSM alternatives and criteria suitable for further analysis. This phase was performed through the Delphi process, taking into consideration the opinions of 28 experts. Phase 3: Use of Multi-criteria Decision Making (MCDM) techniques, namely the Analytic Hierarchy Process (AHP) and Fuzzy Analytic Hierarchy Process (FAHP), to evaluate and rank the identified DSM alternatives and criteria. This was done using pairwise comparisons of 17 experts to evaluate the criteria and alternatives for the buildings (office, religious and school). The research showed that the experts identified six alternative technologies and five criteria for the selection and evaluation of governmental buildings (office, religious and school). After performing the three phases of this research project, a set of criteria and alternatives were ranked based on the information gathered from every group of experts. It was found that reduction in consumption, capital cost and ease of implementation were the three most recommended criteria for the selection of DSM technologies in Kuwait government buildings while high efficiency lighting and programmable thermostats were identified as the most recommended DSM technologies for these buildings. An important aspect of this research is that unlike engineering approaches which sometimes depend on expensive test equipment or, often for building design, expensive computer modelling exercises, the proposed framework can be easily adopted by anyone without any significant financial cost. The FAHP approach was also tested and its results compared with those of AHP. There was a slight difference between using AHP and FAHP in terms of ranking the criteria and alternatives but that the difference barely affects the ranking. It was found that the AHP provides a convenient MCDM approach for solving the complex problem of selecting the optimal DSM options for buildings. The contributions of this thesis are the development of a novel framework for systematic selection and ranking of DSM technologies in different types of buildings using the Delphi method and AHP; the identification of the most important DSM technologies and criteria for their selection for three types of governmental buildings in Kuwait; and establishing that results from using AHP and FAHP for the selection of appropriate DSM measures in these buildings are almost identical, so use of AHP is likely to be sufficient in most building studies of this type.

<p>In the recent decades, therehave been frequent conflicts between groundwater waterresources and environmentally hazardous activities. Newmethodologies for aiding decision-making in groundwater impactassessment and protection areneeded and in which issues ofincreased awareness, better understanding of the groundwaterresources processes, and validation of predictive mathematicalmodels are addressed.</p><p>A framework fordecision–aid, based on predictive simulations that a)predicts the environmental impacts b) provides the totaleconomical value c) visualises the impacts and the groundwaterproperties and d) describes the uncertainties in the results isproposed herein. The framework can be applied in environmentalimpact assessments, strategic environmental assessments andprotection and management of water resources. The results ofthe model are used as feedback for determining new scenarios,depending on the required uncertainties, and if the plannedactivity is sustainable, and/or fulfils the legislative andpolicy measures. This framework is applied to a particular casestudy, Nybroåsen, in the south-eastern part of Sweden,where the highway E22 is constructed through the importantglaciofluvial esker aquifer, passing the protection zone of thewater supply for the Kalmar municipality.</p><p>The impacts from the new highwayand the existing road have been predicted by two-dimensionalphysically based time-variant flow and solute groundwatermodelling. The results, breakthrough curves of contaminantconcentration in wells and maps of concentration distributions,as well as travel times, flow paths, and capture zones forwells determined by particle tracking have been presented.</p><p>The constructed model of theNybroåsen study area was calibrated by comparing observedand simulated groundwater levels for 15 observation wells forten years of measurements. The model has been evaluated bothgraphically and numerically and the calibration target wasfulfilled for 13 of the 15 observation wells. The model workincludes investigations of the catchment information, a waterbalance study, simulation of the groundwater recharge,consideration of the unsaturated zone by a numerical columnsimulation, and sensitivity analysis.</p><p>From the sensitivity analysis ofthe flow and transport parameters, it has been shown that theuncertainties are mainly due to the hydraulic conductivity.Comparison of the derived conductivity from the steady-stateautomatic calibration and the time-variant calibration showedthat there are major differences in the derived parameters,which illustrates the importance of a time dependentcalibration over both wet and dry periods and in more than onepoint in the area of interest of the model predictions.</p><p>In addition, a multi-criteriadecision analysis has been carried out for four roadalternatives (including the new highway E22) and the existingroad in the case study concerned. The multi-criteria decisionaid is applied as an illustration of how it can be used in thestudy area to identify a) interest groups of actors and theirconcerns b) ranking of alternative road scenarios according toactors’preferences and c) coalition groups of actors<i>i.e.</i>groups that have similar views with regard to theroad alternatives.</p><p><b>Keywords:</b>Physically-based groundwater modelling,contamination, flow and solute transport, glaciofluvialdeposits, Nybroåsen, Sweden, and multi-criteriadecision-aid.</p>

Energy access remains a significant challenge in nations lacking access to resources and strong infrastructure systems, creating barriers to economic development and to increased standards of living. Small scale biomass gasification energy (BGE) systems have been developed to meet energy needs in rural areas, creating synergies between agricultural and agro-forestry systems through utilization of biomass feedstock for energy generation. The sustainability of such systems requires sophisticated planning and coordination of the biomass supply chain. The goal of this thesis is to investigate and improve structural and process related characteristics of sustainability assessments for small scale bio-energy systems, specifically focusing on establishment and management of biomass supply chains through the development and dissemination of a generic sustainability assessment framework for biomass supply chains of small-scale BGE systems in rural East Africa. Building on a preliminary sustainability assessment framework (Christensen, 2013; Joerg, 2013) this research develops an assessment tool designed to capture sustainability requirements of the biomass supply chain in the ecological, social, and economic spheres through testing on three case studies in rural Uganda. Application and analysis of a preliminary framework on pilot projects in a rural east African context using Multi Criteria Decision Analysis (MCDA) methodologies contributes to development of strategies for energy system analysis and building stakeholder capacity to incorporate social, economic, and environmental considerations. The assessment process is outlined, including scoring, data collection, contextual considerations. Model application is discussed, including the impact of weighting on decision outcomes, uncertainty management, sensitivity analysis, and identification of tradeoffs among criteria. Finally, discussion of tool usefulness verses usability contributes to bridging academic research with practitioner priorities.