Identifying rural disadvantage using a multiday travel diary

This paper identifies transport disadvantage using a 7 day activity-travel diary data from two rural case study areas. A composite participation index (PI) measure was developed for this study based on six indices measuring elements of travel and activity participation. Using the index the paper then goes on to compare these results, with the results obtained from other more traditional indicators used to identify transport disadvantage. These indicators are related to the size of activity space such as unique network distance travelled, number of unique locations visited, activity space area, activity duration, and fullness (shape) of activity spaces. The weaknesses of these indicator based measures are that: firstly, they do not take into account the relativity of the measure between different areas i.e. travel distance in terms of the wider context of available activities within an area; and secondly, these indicators are multi-dimensional and each represents a different qualitative aspect of travel and activity participation. As a result, six individual indices were developed to overcome these problems. These include: participation count index, participation length index, participation area index, participation duration index, participation type index, and participation frequency index. These are then aggregated to assess the relative performance in terms of these different indices and identify the nature of transport disadvantage. GIS was used to visualise individual travel patterns and to derive scores for both the indicator based measures and the index based measures. Factor analysis was conducted to derive weights of the individual indices to form the composite index measure. From this analysis, two intermediate indices were also derived using the underlying factors of the data related to these indices. Using the scores of all these measures, multiple regression analyses were conducted to identify patterns of transport disadvantage.

Multi-sensor data fusion for UAV navigation during landing operations

This paper presents a practical framework to synthesize multi-sensor navigation information for localization of a rotary-wing unmanned aerial vehicle (RUAV) and estimation of unknown ship positions when the RUAV approaches the landing deck. The estimation performance of the visual tracking sensor can also be improved through integrated navigation. Three different sensors (inertial navigation, Global Positioning System, and visual tracking sensor) are utilized complementarily to perform the navigation tasks for the purpose of an automatic landing. An extended Kalman filter (EKF) is developed to fuse data from various navigation sensors to provide the reliable navigation information. The performance of the fusion algorithm has been evaluated using real ship motion data. Simulation results suggest that the proposed method can be used to construct a practical navigation system for a UAV-ship landing system.

Identifying interests of web users for effective recommendations

Search log data is multi dimensional data consisting of number of searches of multiple users with many searched parameters. This data can be used to identify a user’s interest in an item or object being searched. Identifying highest interests of a Web user from his search log data is a complex process. Based on a user’s previous searches, most recommendation methods employ two-dimensional models to find relevant items. Such items are then recommended to a user. Two-dimensional data models, when used to mine knowledge from such multi dimensional data may not be able to give good mappings of user and his searches. The major problem with such models is that they are unable to find the latent relationships that exist between different searched dimensions. In this research work, we utilize tensors to model the various searches made by a user. Such high dimensional data model is then used to extract the relationship between various dimensions, and find the prominent searched components. To achieve this, we have used popular tensor decomposition methods like PARAFAC, Tucker and HOSVD. All experiments and evaluation is done on real datasets, which clearly show the effectiveness of tensor models in finding prominent searched components in comparison to other widely used two-dimensional data models. Such top rated searched components are then given as recommendation to users.

A task-oriented approach to search engine usability studies

Usability is a multi-dimensional characteristic of a computer system. This paper focuses on usability as a measurement of interaction between the user and the system. The research employs a task-oriented approach to evaluate the usability of a meta search engine. This engine encourages and accepts queries of unlimited size expressed in natural language. A variety of conventional metrics developed by academic and industrial research, including ISO standards,, are applied to the information retrieval process consisting of sequential tasks. Tasks range from formulating (long) queries to interpreting and retaining search results. Results of the evaluation and analysis of the operation log indicate that obtaining advanced search engine results can be accomplished simultaneously with enhancing the usability of the interactive process. In conclusion, we discuss implications for interactive information retrieval system design and directions for future usability research. © 2008 Academy Publisher.

A people-to-people recommendation system using Tensor Space Models

Existing recommendation systems often recommend products to users by capturing the item-to-item and user-to-user similarity measures. These types of recommendation systems become inefficient in people-to-people networks for people to people recommendation that require two way relationship. Also, existing recommendation methods use traditional two dimensional models to find inter relationships between alike users and items. It is not efficient enough to model the people-to-people network with two-dimensional models as the latent correlations between the people and their attributes are not utilized. In this paper, we propose a novel tensor decomposition-based recommendation method for recommending people-to-people based on users profiles and their interactions. The people-to-people network data is multi-dimensional data which when modeled using vector based methods tend to result in information loss as they capture either the interactions or the attributes of the users but not both the information. This paper utilizes tensor models that have the ability to correlate and find latent relationships between similar users based on both information, user interactions and user attributes, in order to generate recommendations. Empirical analysis is conducted on a real-life online dating dataset. As demonstrated in results, the use of tensor modeling and decomposition has enabled the identification of latent correlations between people based on their attributes and interactions in the network and quality recommendations have been derived using the 'alike' users concept.

Value co-creation in social marketing wellness services

Customer perceived value is concerned with the experiences of consumers when using a service and is often referred to in the context of service provision or on the basis of service quality (Auh, et al., 2007; Chang, 2008; Jackson, 2007; Laukkanen, 2007; Padgett & Mulvey, 2007; Shamdasani, Mukherjee & Malhotra, 2008). Understanding customer perceived value has benefits for social marketing and allows scholars and practitioners alike to identify why consumers engage in positive social behaviours through the use of services. Understanding consumers’ use of wellness services in particular is important, because the use of wellness services demonstrates the fulfilment of social marketing aims; performing pro-active, positive social behaviours that are of benefit to the individual and to society (Andreasen, 1994). As consumers typically act out of self-interest (Rothschild, 1999), this research posits that a value proposition must be made to consumers in order to encourage behavioural change. Thus, this research seeks to identify how value is created for consumers of wellness services in social marketing. This results in the overall research question of this research: How is value created in social marketing wellness services? A traditional method towards understanding value has been the adoption of an economic approach, which considers the utility gained and where value is a direct outcome of a cost-benefit analysis (Payne & Holt, 1999). However, there has since been a shift towards the adoption of an experiential approach in understanding value. This experiential approach considers the consumption experience of the consumer which extends beyond the service exchange and includes pre- and post-consumption stages (Russell-Bennett, Previte & Zainuddin, 2009). As such, this research uses an experiential approach to identify the value that exists in social marketing wellness services. Four dimensions of value have been commonly conceptualised and identified in the commercial marketing literature; functional, emotional, social, and altruistic value (Holbrook, 1994; Sheth, Newman & Gross, 1991; Sweeney & Soutar, 2001). It is not known if these value dimensions also exist in social marketing. In addition, sources of value said to influence value dimensions have been conceptualised in the literature. Sources of value such as information, interaction, environment, service, customer co-creation, and social mandate have been conceptually identified both in the commercial and social marketing literature (Russell-Bennet, Previte & Zainuddin, 2009; Smith & Colgate, 2007). However, it is not clear which sources of value contribute to the creation of value for users of wellness services. Thus, this research seeks to explore these relationships. This research was conducted using a wellness service context, specifically breast cancer screening services. The primary target consumer of these services is women aged 50 to 69 years old (inclusive) who have never been diagnosed with breast cancer. It is recommended that women in this target group have a breast screen every 2 years in order to achieve the most effective medical outcomes from screening. A two-study mixed method approach was utilised. Study 1 was a qualitative exploratory study that analysed individual-depth interviews with 25 information-rich respondents. The interviews were transcribed verbatim and analysed using NVivo 8 software. The qualitative results provided evidence of the existence of the four value dimensions in social marketing. The results also allowed for the development of a typology of experiential value by synthesising current understanding of the value dimensions, with the activity aspects of experiential value identified by Holbrook (1994) and Mathwick, Malhotra and Rigdon (2001). The qualitative results also provided evidence for the existence of sources of value in social marketing, namely information, interaction, environment and consumer participation. In particular, a categorisation of sources of value was developed as a result of the findings from Study 1, which identify organisational, consumer, and third party sources of value. A proposed model of value co-creation and a set of hypotheses were developed based on the results of Study 1 for further testing in Study 2. Study 2 was a large-scale quantitative confirmatory study that sought to test the proposed model of value co-creation and the hypotheses developed. An online-survey was administered Australia-wide to women in the target audience. A response rate of 20.1% was achieved, resulting in a final sample of 797 useable responses after removing ineligible respondents. Reliability and validity analyses were conducted on the data, followed by Exploratory Factor Analysis (EFA) in PASW18, followed by Confirmatory Factor Analysis (CFA) in AMOS18. Following the preliminary analyses, the data was subject to Structural Equation Modelling (SEM) in AMOS18 to test the path relationships hypothesised in the proposed model of value creation. The SEM output revealed that all hypotheses were supported, with the exception of one relationship which was non-significant. In addition, post hoc tests revealed seven further significant non-hypothesised relationships in the model. The quantitative results show that organisational sources of value as well as consumer participation sources of value influence both functional and emotional dimensions of value. The experience of both functional and emotional value in wellness services leads to satisfaction with the experience, followed by behavioural intentions to perform the behaviour and use the service again. One of the significant non-hypothesised relationships revealed that emotional value leads to functional value in wellness services, providing further empirical evidence that emotional value features more prominently than functional value for users of wellness services. This research offers several contributions to theory and practice. Theoretically, this research addresses a gap in the literature by using social marketing theory to provide an alternative method of understanding individual behaviour in a domain that has been predominantly investigated in public health. This research also clarifies the concept of value and offers empirical evidence to show that value is a multi-dimensional construct with separate and distinct dimensions. Empirical evidence for a typology of experiential value, as well as a categorisation of sources of value is also provided. In its practical contributions, this research identifies a framework that is the value creation process and offers health services organisations a diagnostic tool to identify aspects of the service process that facilitate the value creation process.

A longitudinal assessment of chronic wound fluid to detect biochemical indicators of healing

Chronic venous leg ulcers are a detrimental health issue plaguing our society, resulting in long term pain, immobility and decreased quality of life for a large proportion of sufferers. The frequency of these chronic wounds has led current research to focus on the wound environment to provide important information regarding the prolonged, fluctuated or static healing patterns of these wounds. Disruption to the normal wound healing process results in release of multiple factors in the wound environment that could correlate to wound chronicity. These biochemical factors can often be detected through non-invasively sampling chronic wound fluid (CWF) from the site of injury. Of note, whilst there are numerous studies comparing acute and chronic wound fluids, there have not been any reports in the literature employing a longitudinal study in order to track biochemical changes in wound fluid as patients transition from a non-healing to healed state. Initially the objective of this study was to identify biochemical changes in CWF associated with wound healing using a proteomic approach. The proteomic approach incorporated a multi-dimensional liquid chromatography fractionation technique coupled with mass spectrometry (MS) to enable identification of proteins present in lower concentrations in CWF. Not surprisingly, many of the proteins identified in wound fluid were acute phase proteins normally expressed during the inflammatory phase of healing. However, the number of proteins positively identified by MS was quite low. This was attributed to the diverse range in concentration of protein species in CWF making it challenging to detect the diagnostically relevant low molecular weight proteins. In view of this, SELDI-TOF MS was also explored as a means to target low molecular weight proteins in sequential patient CWF samples during the course of healing. Unfortunately, the results generated did not yield any peaks of interest that were altered as wounds transitioned to a healed state. During the course of proteomic assessment of CWF, it became evident that a fraction of non-proteinaceous compounds strongly absorbed at 280 nm. Subsequent analyses confirmed that most of these compounds were in fact part of the purine catabolic pathway, possessing distinctive aromatic rings and which results in high absorbance at 254 nm. The accumulation of these purinogenic compounds in CWF suggests that the wound bed is poorly oxygenated resulting in a switch to anaerobic metabolism and consequently ATP breakdown. In addition, the presence of the terminal purine catabolite, uric acid (UA), indicates that the enzyme xanthine oxidoreductase (XOR) catalyses the reaction of hypoxanthine to xanthine and finally to UA. More importantly, the studies provide evidence for the first time of the exogenous presence of XOR in CWF. XOR is the only enzyme in humans capable of catalysing the production of UA in conjunction with a burst of the highly reactive superoxide radical and other oxidants like H2O2. Excessive release of these free radicals in the wound environment can cause cellular damage disrupting the normal wound healing process. In view of this, a sensitive and specific assay was established for monitoring low concentrations of these catabolites in CWF. This procedure involved combining high performance liquid chromatography (HPLC) with tandem mass spectrometry and multiple reaction monitoring (MRM). This application was selective, using specific MRM transitions and HPLC separations for each analyte, making it ideal for the detection and quantitation of purine catabolites in CWF. The results demonstrated that elevated levels of UA were detected in wound fluid obtained from patients with clinically worse ulcers. This suggests that XOR is active in the wound site generating significant amounts of reactive oxygen species (ROS). In addition, analysis of the amount of purine precursors in wound fluid revealed elevated levels of purine precursors in wound fluid from patients with less severe ulcers. Taken together, the results generated in this thesis suggest that monitoring changes of purine catabolites in CWF is likely to provide valuable information regarding the healing patterns of chronic venous leg ulcers. XOR catalysis of purine precursors not only provides a method for monitoring the onset, prognosis and progress of chronic venous leg ulcers, but also provides a potential therapeutic target by inhibiting XOR, thus blocking UA and ROS production. Targeting a combination of these purinogenic compounds and XOR could lead to the development of novel point of care diagnostic tests. Therefore, further investigation of these processes during wound healing will be worthwhile and may assist in elucidating the pathogenesis of this disease state, which in turn may lead to the development of new diagnostics and therapies that target these processes.

The use of virtual prototyping for hazard identification in the early design stage

Purpose: The construction industry is well known for its high accident rate and many practitioners consider a preventative approach to be the most important means of bringing about improvements. This paper addresses previous research and the weaknesses of existing preventative approaches and a new application is described and illustrated involving the use of a multi-dimensional simulation tool - Construction Virtual Prototyping (CVP). Methodology: A literature review was conducted to investigate previous studies of hazard identification and safety management and to develop the new approach. Due to weaknesses in current practice, the research study explored the use of computer simulation techniques to create virtual environments where users can explore and identify construction hazards. Specifically, virtual prototyping technology was deployed to develop typical construction scenarios in which unsafe or hazardous incidents occur. In a case study, the users’ performance was evaluated their responses to incidents within the virtual environment and the effectiveness of the computer simulation system established though interviews with the safety project management team. Findings: The opinions and suggestions provided by the interviewees led to the initial conclusion that the simulation tool was useful in assisting the safety management team’s hazard identification process during the early design stage. Originality: The research introduces an innovative method to support the management teams’ reviews of construction site safety. The system utilises three-dimensional modelling and four-dimensional simulation of worker behaviour, a configuration that has previously not been employed in construction simulations. An illustration of the method’s use is also provided, together with a consideration of its strengths and weaknesses.

The NetWorkPlace(TM) Phenomenon: any time and any place - reality or a seductive myth?

A new spatial logic encompassing redefined concepts of time and place, space and distance, requires a comprehensive shift in the approach to designing workplace environments for today’s adaptive, collaborative organizations operating in a dynamic business world. Together with substantial economic and cultural shifts and an increased emphasis on lifestyle considerations, the advances in information technology have prompted a radical re-ordering of organizational relationships and the associated structures, processes, and places of doing business. Within the duality of space and an augmentation of the traditional notions of place, organizational and institutional structures pose new challenges for the design professions. The literature reveals that there has always been a mono-organizational focus in relation to workplace design strategies and the burgeoning trend towards inter-organizational collaboration, enabled the identification of a gap in the knowledge relative to workplace design. The NetWorkPlaceTM© constitutes a multi-dimensional concept having the capacity to deal with the fluidity and ambiguity characteristic of the network context, as both a topic of research and the way of going about it.

Extending and validating the is-impact model in Saudi Arabia : accounting for computer network quality

Organizations from every industry sector seek to enhance their business performance and competitiveness through the deployment of contemporary information systems (IS), such as Enterprise Systems (ERP). Investments in ERP are complex and costly, attracting scrutiny and pressure to justify their cost. Thus, IS researchers highlight the need for systematic evaluation of information system success, or impact, which has resulted in the introduction of varied models for evaluating information systems. One of these systematic measurement approaches is the IS-Impact Model introduced by a team of researchers at Queensland University of technology (QUT) (Gable, Sedera, & Chan, 2008). The IS-Impact Model is conceptualized as a formative, multidimensional index that consists of four dimensions. Gable et al. (2008) define IS-Impact as "a measure at a point in time, of the stream of net benefits from the IS, to date and anticipated, as perceived by all key-user-groups" (p.381). The IT Evaluation Research Program (ITE-Program) at QUT has grown the IS-Impact Research Track with the central goal of conducting further studies to enhance and extend the IS-Impact Model. The overall goal of the IS-Impact research track at QUT is "to develop the most widely employed model for benchmarking information systems in organizations for the joint benefit of both research and practice" (Gable, 2009). In order to achieve that, the IS-Impact research track advocates programmatic research having the principles of tenacity, holism, and generalizability through extension research strategies. This study was conducted within the IS-Impact Research Track, to further generalize the IS-Impact Model by extending it to the Saudi Arabian context. According to Hofsted (2012), the national culture of Saudi Arabia is significantly different from the Australian national culture making the Saudi Arabian culture an interesting context for testing the external validity of the IS-Impact Model. The study re-visits the IS-Impact Model from the ground up. Rather than assume the existing instrument is valid in the new context, or simply assess its validity through quantitative data collection, the study takes a qualitative, inductive approach to re-assessing the necessity and completeness of existing dimensions and measures. This is done in two phases: Exploratory Phase and Confirmatory Phase. The exploratory phase addresses the first research question of the study "Is the IS-Impact Model complete and able to capture the impact of information systems in Saudi Arabian Organization?". The content analysis, used to analyze the Identification Survey data, indicated that 2 of the 37 measures of the IS-Impact Model are not applicable for the Saudi Arabian Context. Moreover, no new measures or dimensions were identified, evidencing the completeness and content validity of the IS-Impact Model. In addition, the Identification Survey data suggested several concepts related to IS-Impact, the most prominent of which was "Computer Network Quality" (CNQ). The literature supported the existence of a theoretical link between IS-Impact and CNQ (CNQ is viewed as an antecedent of IS-Impact). With the primary goal of validating the IS-Impact model within its extended nomological network, CNQ was introduced to the research model. The Confirmatory Phase addresses the second research question of the study "Is the Extended IS-Impact Model Valid as a Hierarchical Multidimensional Formative Measurement Model?". The objective of the Confirmatory Phase was to test the validity of IS-Impact Model and CNQ Model. To achieve that, IS-Impact, CNQ, and IS-Satisfaction were operationalized in a survey instrument, and then the research model was assessed by employing the Partial Least Squares (PLS) approach. The CNQ model was validated as a formative model. Similarly, the IS-Impact Model was validated as a hierarchical multidimensional formative construct. However, the analysis indicated that one of the IS-Impact Model indicators was insignificant and can be removed from the model. Thus, the resulting Extended IS-Impact Model consists of 4 dimensions and 34 measures. Finally, the structural model was also assessed against two aspects: explanatory and predictive power. The analysis revealed that the path coefficient between CNQ and IS-Impact is significant with t-value= (4.826) and relatively strong with â = (0.426) with CNQ explaining 18% of the variance in IS-Impact. These results supported the hypothesis that CNQ is antecedent of IS-Impact. The study demonstrates that the quality of Computer Network affects the quality of the Enterprise System (ERP) and consequently the impacts of the system. Therefore, practitioners should pay attention to the Computer Network quality. Similarly, the path coefficient between IS-Impact and IS-Satisfaction was significant t-value = (17.79) and strong â = (0.744), with IS-Impact alone explaining 55% of the variance in Satisfaction, consistent with results of the original IS-Impact study (Gable et al., 2008). The research contributions include: (a) supporting the completeness and validity of IS-Impact Model as a Hierarchical Multi-dimensional Formative Measurement Model in the Saudi Arabian context, (b) operationalizing Computer Network Quality as conceptualized in the ITU-T Recommendation E.800 (ITU-T, 1993), (c) validating CNQ as a formative measurement model and as an antecedent of IS Impact, and (d) conceptualizing and validating IS-Satisfaction as a reflective measurement model and as an immediate consequence of IS Impact. The CNQ model provides a framework to perceptually measure Computer Network Quality from multiple perspectives. The CNQ model features an easy-to-understand, easy-to-use, and economical survey instrument.

Investigating the success of operational business process management systems

Business process management systems (BPMS) belong to a class of enterprise information systems that are characterized by the dependence on explicitly modeled process logic. Through the process logic, it is relatively easy to manage explicitly the routing and allocation of work items along a business process through the system. Inspired by the DeLone and McLean framework, we theorize that these process-aware system features are important attributes of system quality, which in turn will elevate key user evaluations such as perceived usefulness, and usage satisfaction. We examine this theoretical model using data collected from four different, mostly mature BPM system projects. Our findings validate the importance of input quality as well as allocation and routing attributes as antecedents of system quality, which, in turn, determines both usefulness and satisfaction with the system. We further demonstrate how service quality and workflow dependency are significant precursors to perceived usefulness. Our results suggest the appropriateness of a multi-dimensional conception of system quality for future research, and provide important design-oriented advice for the design and configuration of BPMSs.

A micro-level indexing model for the assessment of sustainable urban ecosystems

During the last several decades, the quality of natural resources and their services have been exposed to significant degradation from increased urban populations combined with the sprawl of settlements, development of transportation networks and industrial activities (Dorsey, 2003; Pauleit et al., 2005). As a result of this environmental degradation, a sustainable framework for urban development is required to provide the resilience of natural resources and ecosystems. Sustainable urban development refers to the management of cities with adequate infrastructure to support the needs of its population for the present and future generations as well as maintain the sustainability of its ecosystems (UNEP/IETC, 2002; Yigitcanlar, 2010). One of the important strategic approaches for planning sustainable cities is „ecological planning‟. Ecological planning is a multi-dimensional concept that aims to preserve biodiversity richness and ecosystem productivity through the sustainable management of natural resources (Barnes et al., 2005). As stated by Baldwin (1985, p.4), ecological planning is the initiation and operation of activities to direct and control the acquisition, transformation, disruption and disposal of resources in a manner capable of sustaining human activities with a minimum disruption of ecosystem processes. Therefore, ecological planning is a powerful method for creating sustainable urban ecosystems. In order to explore the city as an ecosystem and investigate the interaction between the urban ecosystem and human activities, a holistic urban ecosystem sustainability assessment approach is required. Urban ecosystem sustainability assessment serves as a tool that helps policy and decision-makers in improving their actions towards sustainable urban development. There are several methods used in urban ecosystem sustainability assessment among which sustainability indicators and composite indices are the most commonly used tools for assessing the progress towards sustainable land use and urban management. Currently, a variety of composite indices are available to measure the sustainability at the local, national and international levels. However, the main conclusion drawn from the literature review is that they are too broad to be applied to assess local and micro level sustainability and no benchmark value for most of the indicators exists due to limited data availability and non-comparable data across countries. Mayer (2008, p. 280) advocates that by stating "as different as the indices may seem, many of them incorporate the same underlying data because of the small number of available sustainability datasets". Mori and Christodoulou (2011) also argue that this relative evaluation and comparison brings along biased assessments, as data only exists for some entities, which also means excluding many nations from evaluation and comparison. Thus, there is a need for developing an accurate and comprehensive micro-level urban ecosystem sustainability assessment method. In order to develop such a model, it is practical to adopt an approach that uses a method to utilise indicators for collecting data, designate certain threshold values or ranges, perform a comparative sustainability assessment via indices at the micro-level, and aggregate these assessment findings to the local level. Hereby, through this approach and model, it is possible to produce sufficient and reliable data to enable comparison at the local level, and provide useful results to inform the local planning, conservation and development decision-making process to secure sustainable ecosystems and urban futures. To advance research in this area, this study investigated the environmental impacts of an existing urban context by using a composite index with an aim to identify the interaction between urban ecosystems and human activities in the context of environmental sustainability. In this respect, this study developed a new comprehensive urban ecosystem sustainability assessment tool entitled the „Micro-level Urban-ecosystem Sustainability IndeX‟ (MUSIX). The MUSIX model is an indicator-based indexing model that investigates the factors affecting urban sustainability in a local context. The model outputs provide local and micro-level sustainability reporting guidance to help policy-making concerning environmental issues. A multi-method research approach, which is based on both quantitative analysis and qualitative analysis, was employed in the construction of the MUSIX model. First, a qualitative research was conducted through an interpretive and critical literature review in developing a theoretical framework and indicator selection. Afterwards, a quantitative research was conducted through statistical and spatial analyses in data collection, processing and model application. The MUSIX model was tested in four pilot study sites selected from the Gold Coast City, Queensland, Australia. The model results detected the sustainability performance of current urban settings referring to six main issues of urban development: (1) hydrology, (2) ecology, (3) pollution, (4) location, (5) design, and; (6) efficiency. For each category, a set of core indicators was assigned which are intended to: (1) benchmark the current situation, strengths and weaknesses, (2) evaluate the efficiency of implemented plans, and; (3) measure the progress towards sustainable development. While the indicator set of the model provided specific information about the environmental impacts in the area at the parcel scale, the composite index score provided general information about the sustainability of the area at the neighbourhood scale. Finally, in light of the model findings, integrated ecological planning strategies were developed to guide the preparation and assessment of development and local area plans in conjunction with the Gold Coast Planning Scheme, which establishes regulatory provisions to achieve ecological sustainability through the formulation of place codes, development codes, constraint codes and other assessment criteria that provide guidance for best practice development solutions. These relevant strategies can be summarised as follows: • Establishing hydrological conservation through sustainable stormwater management in order to preserve the Earth’s water cycle and aquatic ecosystems; • Providing ecological conservation through sustainable ecosystem management in order to protect biological diversity and maintain the integrity of natural ecosystems; • Improving environmental quality through developing pollution prevention regulations and policies in order to promote high quality water resources, clean air and enhanced ecosystem health; • Creating sustainable mobility and accessibility through designing better local services and walkable neighbourhoods in order to promote safe environments and healthy communities; • Sustainable design of urban environment through climate responsive design in order to increase the efficient use of solar energy to provide thermal comfort, and; • Use of renewable resources through creating efficient communities in order to provide long-term management of natural resources for the sustainability of future generations.

Augmenting analytical CRM strategies with social BI

Large communities built around social media on the Internet offer an opportunity to augment analytical customer relationship management (CRM) strategies. The purpose of this paper is to provide direction to advance the conceptual design of business intelligence (BI) systems for implementing CRM strategies. After introducing social CRM and social BI as emerging fields of research, the authors match CRM strategies with a re-engineered conceptual data model of Facebook in order to illustrate the strategic value of these data. Subsequently, the authors design a multi-dimensional data model for social BI and demonstrate its applicability by designing management reports in a retail scenario. Building on the service blueprinting framework, the authors propose a structured research agenda for the emerging field of social BI.

Integration of sentiment analysis into customer relational model : the importance of feature ontology and synonym

Online business or Electronic Commerce (EC) is getting popular among customers today, as a result large number of product reviews have been posted online by the customers. This information is very valuable not only for prospective customers to make decision on buying product but also for companies to gather information of customers’ satisfaction about their products. Opinion mining is used to capture customer reviews and separated this review into subjective expressions (sentiment word) and objective expressions (no sentiment word). This paper proposes a novel, multi-dimensional model for opinion mining, which integrates customers’ characteristics and their opinion about any products. The model captures subjective expression from product reviews and transfers to fact table before representing in multi-dimensions named as customers, products, time and location. Data warehouse techniques such as OLAP and Data Cubes were used to analyze opinionated sentences. A comprehensive way to calculate customers’ orientation on products’ features and attributes are presented in this paper.

A multi-level ecological model of psychotropic prescribing to adults with intellectual disability

Purpose – Simple linear accounts of prescribing do not adequately address reasons “why” doctors prescribe psychotropic medication to people with intellectual disability (ID). Greater understanding of the complex array of factors that influence decisions to prescribe is needed. Design/methodology/approach – After consideration of a number of conceptual frameworks that have potential to better understand prescribing of psychotropic medication to adults with ID, an ecological model of prescribing was developed. A case study is used to outline how the model can provide greater understanding of prescribing processes. Findings – The model presented aims to consider the complexity and multi-dimensional nature of community-based psychotropic prescribing to adults with ID. The utility of the model is illustrated through a consideration of the case study. Research limitations/implications – The model presented is conceptual and is as yet untested. Practical implications – The model presented aims to capture the complexity and multi-dimensional nature of community-based psychotropic prescribing to adults with ID. The model may provide utility for clinicians and researchers as they seek clarification of prescribing decisions. Originality/value – The paper adds valuable insight into factors influencing psychotropic prescribing to adults with ID. The ecological model of prescribing extends traditional analysis that focuses on patient characteristics and introduces multi-level perspectives that may provide utility for clinicians and researchers.