Implementing green business processes : the importance of functional affordances of information systems

An environmentally sustainable and thus green business process is one that delivers organizational value whilst also exerting a minimal impact on the natural environment. Recent works from the field of Information Systems (IS) have argued that information systems can contribute to the design and implementation of sustainable business processes. While prior research has investigated how information systems can be used in order to support sustainable business practices, there is still a void as to the actual changes that business processes have to undergo in order to become environmentally sustainable, and the specific role that information systems play in enabling this change. In this paper, we provide a conceptualization of environmentally sustainable business processes, and discuss the role of functional affordances of information systems in enabling both incremental and radical changes in order to make processes environmentally sustainable. Our conceptualization is based on (a) a fundamental definition of the concept of environmental sustainability, grounded in two basic components:the environmental source and sink functions of any project or activity, and (b) the concept of functional affordances, which describe the potential uses originating in the material properties of information systems in relation to their use context. In order to illustrate the application of our framework and provide a first evaluation, we analyse two examples from prior research where information systems impacted on the sustainability of business processes.

Investing for impact : Constructing a better built environment

This publication, Investing for Impact, is a key outcome of Project 2.7 Leveraging R&D Investment for the Australian Built Environment. This information will be included in a more comprehensive book being prepared for publication in 2014 (Taylor and Francis). It draws together research findings and case studies from CIB Task Group 85 members from across the globe, highlighting their diversity and similarities. The evaluation of international case studies on the role and impact of R&D on national development has allowed us to demonstrate examples from different sectors of the built environment of R&D investment models that provide return on investment and other benefits for companies, governments and the general community.

Concepts, water and reflections on practice

This paper discusses the nature of the conceptual structure in art practice, by example. It draws on insights gained from a practice based research (PBR) approach to making art. The PBR methods used include Reflective Practice and are briefly described. They have informed an understanding of the conceptual structure as an instance of problem framing. This is demonstrated by two creative examples, taken from two interactive artworks. These were informed by an evolving conceptual structure concerned with water.

Rock, paper, scissors : reflective practice for design process in the novice landscape architect

We describe a pedagogical approach that addresses challenges in design education for novices. These include an inability to frame new problems and limited-to-no design capability or domain knowledge. Such challenges can reduce student engagement with design practice, cause derivative design solutions as well as the inappropriate simplification of design assignments and assessment criteria by educators. We argue that a curriculum that develops the student’s design process will enable them to deal with the uncertain and dynamic situations that characterise design. We describe how this may be achieved and explain our pedagogical approach in terms of methods from Reflective Practice and theories of abstraction and creativity. We present a landscape architecture unit, recently taught, as an example. It constitutes design exercises that require little domain or design expertise to support the development of conceptual thinking and a design rationale. We show how this approach (a) leveraged the novice’s existing spatial and thinking skills while (b) retaining contextually-rich design situations. Examples of the design exercises taught are described along with samples of student work. The assessment rationale is also presented and explained. Finally, we conclude by reflecting on how this approach relates to innovation, sustainability and other disciplines.

Critical Factors for Sustainable Post Natural Disaster Reconstruction : Chinese Data

While scientists continue to explore the level of climate change impact to new weather patterns and our environment in general, there have been some devastating natural disasters worldwide in the last two decades. Indeed natural disasters are becoming a major concern in our society. Yet in many previous examples, our reconstruction efforts only focused on providing short-term necessities. How to develop resilience in the long run is now a highlight for research and industry practice. This paper introduces a research project aimed at exploring the relationship between resilience building and sustainability in order to identify key factors during reconstruction efforts. From extensive literature study, the authors considered the inherent linkage between the two issues as evidenced from past research. They found that sustainability considerations can improve the level of resilience but are not currently given due attention. Reconstruction efforts need to focus on resilience factors but as part of urban development, they must also respond to the sustainability challenge. Sustainability issues in reconstruction projects need to be amplified, identified, processed, and managed properly. On-going research through empirical study aims to establish critical factors (CFs) for stakeholders in disaster prone areas to plan for and develop new building infrastructure through holistic considerations and balanced approaches to sustainability. A questionnaire survey examined a range of potential factors and the subsequent data analysis revealed six critical factors for sustainable Post Natural Disaster Reconstruction that include: considerable building materials and construction methods, good governance, multilateral coordination, appropriate land-use planning and policies, consideration of different social needs, and balanced combination of long-term and short-term needs. Findings from this study should have an influence on policy development towards Post Natural Disaster Reconstruction and help with the achievement of sustainable objectives.

Evaluating Communication for Development : A Framework for Social Change

Evaluating Communication for Development presents a comprehensive framework for evaluating communication for development (C4D). This framework combines the latest thinking from a number of fields in new ways. It critiques dominant instrumental, accountability-based approaches to development and evaluation and offers an alternative holistic, participatory, mixed methods approach based on systems and complexity thinking and other key concepts. It maintains a focus on power, gender and other differences and social norms. The authors have designed the framework as a way to focus on achieving sustainable social change and to continually improve and develop C4D initiatives. The benefits and rigour of this approach are supported by examples and case studies from a number of action research and evaluation capacity development projects undertaken by the authors over the past fifteen years. Building on current arguments within the fields of C4D and development, the authors reinforce the case for effective communication being a central and vital component of participatory forms of development, something that needs to be appreciated by decision makers. They also consider ways of increasing the effectiveness of evaluation capacity development from grassroots to management level in the development context, an issue of growing importance to improving the quality, effectiveness and utilisation of monitoring and evaluation studies in this field. The book includes a critical review of the key approaches, methodologies and methods that are considered effective for planning evaluation, assessing the outcomes of C4D, and engaging in continuous learning. This rigorous book is of immense theoretical and practical value to students, scholars, and professionals researching or working in development, communication and media, applied anthropology, and evaluation and program planning.

Large-scale community projects in regional Queensland : unlocking creative potential and community identity : Artspoken Queensland Regional Arts and Culture Conference 2011

In this presentation, renowned arts practitioner, Sean Mee, and Nigel Lavender, Executive Director of the Queensland Music Festival, talk about how community arts practice can be used to build cultural captial in communities, using examples such large-scale musicals such as The Road We're ON (Charleville) and Behind the Cand (Bowen), Mee and Lavender highlight the importance of community-driven narrative and particiaption.

Critical factors for successful housing reconstruction projects following a major disaster

Post–disaster reconstruction projects are often considered ineffectual or unproductive because on many occasions in the past they have performed extremely poorly during post-contract occupation, or have failed altogether to deliver acceptable outcomes. In some cases, these projects have already failed even before their completion, leading many sponsor aid organisations to hold these projects up as examples of how not to deliver housing reconstruction. Research into some previous unsuccessful projects has revealed that often the lack of adequate knowledge regarding the context and complexity involved in the implementation of these projects is generally responsible for their failure. Post-disaster reconstruction projects are certainly very complex in nature, often very context-specific and they can vary widely in magnitude. Despite such complexity, reconstruction projects can still have a high likelihood of success if adequate consideration is given to the importance of factors which are known to positively influence reconstruction efforts. Good outcomes can be achieved when planners and practitioners ensure best practices are embedded in the design of reconstruction projects at the time reconstruction projects they are first instigated. This paper outlines and discusses factors that significantly contribute to the successful delivery of post-disaster housing reconstruction projects.

Bayesian computation via empirical likelihood

Approximate Bayesian computation has become an essential tool for the analysis of complex stochastic models when the likelihood function is numerically unavailable. However, the well-established statistical method of empirical likelihood provides another route to such settings that bypasses simulations from the model and the choices of the approximate Bayesian computation parameters (summary statistics, distance, tolerance), while being convergent in the number of observations. Furthermore, bypassing model simulations may lead to significant time savings in complex models, for instance those found in population genetics. The Bayesian computation with empirical likelihood algorithm we develop in this paper also provides an evaluation of its own performance through an associated effective sample size. The method is illustrated using several examples, including estimation of standard distributions, time series, and population genetics models.

Managing memory and reducing I/O cost for correlation matrix calculation in bioinformatics

The generation of a correlation matrix from a large set of long gene sequences is a common requirement in many bioinformatics problems such as phylogenetic analysis. The generation is not only computationally intensive but also requires significant memory resources as, typically, few gene sequences can be simultaneously stored in primary memory. The standard practice in such computation is to use frequent input/output (I/O) operations. Therefore, minimizing the number of these operations will yield much faster run-times. This paper develops an approach for the faster and scalable computing of large-size correlation matrices through the full use of available memory and a reduced number of I/O operations. The approach is scalable in the sense that the same algorithms can be executed on different computing platforms with different amounts of memory and can be applied to different problems with different correlation matrix sizes. The significant performance improvement of the approach over the existing approaches is demonstrated through benchmark examples.

Stratospheric dust collections : valuable resources for space and atmospheric scientists

Collections of solid particles from the Earths' stratosphere have been a significant part of atmospheric research programs since 1965 [1], but it has only been in the past decade that space-related disciplines have provided the impetus for a continued interest in these collections. Early research on specific particle types collected from the stratosphere established that interplanetary dust particles (IDP's) can be collected efficiently and in reasonable abundance using flat-plate collectors [2-4]. The tenacity of Brownlee and co-workers in this subfield of cosmochemistry has led to the establishment of a successful IDP collection and analysis program (using flat-plate collectors on high-flying aircraft) based on samples available for distribution from Johnson Space Center [5]. Other stratospheric collections are made, but the program at JSC offers a unique opportunity to study well-documented, individual particles (or groups of particles) from a wide variety of sources [6]. The nature of the collection and curation process, as well as the timeliness of some sampling periods [7], ensures that all data obtained from stratospheric particles is a valuable resource for scientists from a wide range of disciplines. A few examples of the uses of these stratospheric dust collections are outlined below.

Two novel numerical methods for solving the two-dimensional fractional Fitzhugh-Nagumo-monodomain model

Fractional mathematical models represent a new approach to modelling complex spatial problems in which there is heterogeneity at many spatial and temporal scales. In this paper, a two-dimensional fractional Fitzhugh-Nagumo-monodomain model with zero Dirichlet boundary conditions is considered. The model consists of a coupled space fractional diffusion equation (SFDE) and an ordinary differential equation. For the SFDE, we first consider the numerical solution of the Riesz fractional nonlinear reaction-diffusion model and compare it to the solution of a fractional in space nonlinear reaction-diffusion model. We present two novel numerical methods for the two-dimensional fractional Fitzhugh-Nagumo-monodomain model using the shifted Grunwald-Letnikov method and the matrix transform method, respectively. Finally, some numerical examples are given to exhibit the consistency of our computational solution methodologies. The numerical results demonstrate the effectiveness of the methods.

Spectral approximations to the fractional integral and derivative

In this paper, the spectral approximations are used to compute the fractional integral and the Caputo derivative. The effective recursive formulae based on the Legendre, Chebyshev and Jacobi polynomials are developed to approximate the fractional integral. And the succinct scheme for approximating the Caputo derivative is also derived. The collocation method is proposed to solve the fractional initial value problems and boundary value problems. Numerical examples are also provided to illustrate the effectiveness of the derived methods.

Numerical approximation for a variable-order nonlinear reaction–subdiffusion equation

Fractional reaction–subdiffusion equations are widely used in recent years to simulate physical phenomena. In this paper, we consider a variable-order nonlinear reaction–subdiffusion equation. A numerical approximation method is proposed to solve the equation. Its convergence and stability are analyzed by Fourier analysis. By means of the technique for improving temporal accuracy, we also propose an improved numerical approximation. Finally, the effectiveness of the theoretical results is demonstrated by numerical examples.