Creating healthy food environments in NSW: A knowledge and evidence synthesis to inform advocacy and action. Seven separate documents across the domains: Food promotion

Reviews and synthesizes evidence to make recommendations on policy actions improve food environments in the area of food promotion for NSW Health

Creating healthy food environments in N.S.W.: A knowledge and evidence synthesis to inform advocacy and action: Food pricing

Reviews and synthesizes evidence to produce evidence-based recommendations on policy actions to improve food pricing for NSW Health

Creating healthy food environments in N.S.W.: A knowledge and evidence synthesis to inform advocacy and action: Food provision

Reviews and synthesizes evidence to produce evidence-based recommendations on policy actions to improve food provision for NSW Health

Creating healthy food environments in NSW: A knowledge and evidence synthesis to inform advocacy and action. Seven separate documents across the domains: Food retail

Reviews and synthesizes nutrition policy actions to improve food retail for NSW Health

Creating healthy food environments in NSW: A knowledge and evidence synthesis to inform advocacy and action. Seven separate documents across the domains: Overview

Summaries evidence across seven domains of potential food policy action to improve food environments and food supply to prevent obesity for NSW Health

Standardization efforts: The relationship between knowledge dimensions, search processes and innovation outcomes

We explore how a standardization effort (i.e., when a firm pursues standards to further innovation) involves different search processes for knowledge and innovation outcomes. Using an inductive case study of Vanke, a leading Chinese property developer, we show how varying degrees of knowledge complexity and codification combine to produce a typology of four types of search process: active, integrative, decentralized and passive, resulting in four types of innovation outcome: modular, radical, incremental and architectural. We argue that when the standardization effort in a firm involves highly codified knowledge, incremental and architectural innovation outcomes are fostered, while modular and radical innovations are hindered. We discuss how standardization efforts can result in a second-order innovation capability, and conclude by calling for comparative research in other settings to understand how standardization efforts can be suited to different types of search process in different industry contexts.

The university and the knowledge network: A new educational model for 21st century learning and employability

The higher education sector is under ongoing pressure to demonstrate quality and efficacy of educational provision, including graduate outcomes. Preparing students as far as possible for the world of professional work has become one of the central tasks of contemporary universities. This challenging task continues to receive significant attention by policy makers and scholars, in the broader contexts of widespread labour market uncertainty and massification of the higher education system (Tomlinson, 2012). In contrast to the previous era of the university, in which ongoing professional employment was virtually guaranteed to university-qualified individuals, contemporary graduates must now be proactive and flexible. They must adapt to a job market that may not accept them immediately, and has continually shifting requirements (Clarke, 2008). The saying goes that rather than seeking security in employment, graduates must now “seek security in employability”. However, as I will argue in this chapter, the current curricular and pedagogic approaches universities adopt, and indeed the core structural characteristics of university-based education, militate against the development of the capabilities that graduates require now and into the future.

Knowledge identification and acquisition in SMEs: Strategically emergent or just ad hoc

Researchers and practitioners have been preoccupied with identifying ways for larger organizations to acquire and manage knowledge, however far less research attention has been directed towards these same pursuits in small and medium-sized enterprises (SMEs). This paper examines how SMEs engage in knowledge identification and acquisition; in particular how they identify knowledge needs and source this knowledge to enhance their business. The research studied six SMEs in Australia and Denmark. Contrary to prevailing assumptions, the findings suggest that SMEs engage in identification and sourcing of critical knowledge, albeit often with less than formal processes. These organizations relied on business plans to direct knowledge activities and ensure balance between long-range planning and flexibility. The results address a lack of empirical evidence about SME approaches to knowledge identification and acquisition, and demonstrate that although SMEs may approach such activities in an informal way, they are nonetheless deliberate and strategic in their knowledge activities.

Knowledge networks and Australian Football League coach development: People of influence

Australian Football League (AFL) generally recognised as the ‘national game’ in Australia has a well established program of coach development. However, research examining AFL coaches’ work and how they learn to perform that work has hitherto not been conducted. The effective preparation of coaches is of prime concern to the AFL and should be informed by an examination of how coaches within the code come to know how to do their coaching work. Therefore, the purpose of this AFL-funded research was to inform coach development programs for current and aspiring AFL coaches.

Knowledge management research in the construction industry: a review

Purpose: Knowledge management (KM) is important to the knowledge-intensive construction industry. The diversified and changing nature of works in this field warrants us to stocktake, identify changes and map out KM research framework for future exploration. Design/methodology/approach: The study involves three aspects. First, three stages of KM research in construction were distinguished in terms of the time distribution of 217 target publications. Major topics in the stages were extracted for understanding the changes of research emphasis from evolutionary perspective. Second, the past works were summed up in a three-dimensional research framework in terms of management organization, managerial methodology and approach, and managerial objective. Finally, potential research orientations in the future were predicted to expand the existing research framework. Findings: It was found that (1) KM research has significantly blossomed in the last two decades with a great potential; (2) major topics of KM were changing in terms of technology, technique, organization, attribute of knowledge and research objectives; (3) past KM studies centred around management organization, managerial methodology and approach, and managerial objective thus a three-dimensional research framework was proposed; (4) within the research framework, team-level, project-level and firm-level KM were studied to achieve project, organizational and competitive objectives by integrated methodologies of information technology, social technique and KM process tool; and (5) nine potential research orientations were predicted corresponding to the three dimensions. Finally, an expanded research framework was proposed to encourage and guide future research works in this field. Research limitations/implications: The paper only focused on the construction industry. The findings need further exploration in order to discover any possible missing important research works which were not published in English or not included in the time period. Originality/value: The paper formed a systematic framework of KM research in construction and predicted the potential research orientations. It provides much value for the researchers who want to understand the past and the future of global KM research in the construction industry.

Coaching knowledge, learning and mentoring in the Australian Football League

Understanding the work of Senior and Assistant Coaches in the AFL is important to better develop the next generation of performance coaches. Hence the focus of this research was to examine the knowledge, competences and learning of senior and assistant coaches in the Australian Football League. Specifically, the research sought to understand the ways in which Senior and Assistant Coaches in the AFL have come to know their “craft” with the particular aim of enhancing future coaching practice. Performance coaching is generally regarded as a cognitive activity and therefore “getting inside the heads” of AFL coaches will assist in our understanding of the complex coaching work in which they are engaged. In-depth interviews provided coaches an opportunity to reflect on their practices and how they learned their craft. Fundamental to this research was an understanding that the AFL and each club within the league be regarded as learning organizations and workplaces where learning takes place. Moreover the process of mentoring is regarded as a central learning process and a significant factor contributing to improved professional coaching practice. This applied research aims to inform coach development in Australian football, the annual review process (quality of performance) of employed coaches, and the recruitment of coaches in the AFL. Improving the quality of coaching in the AFL will, in turn, improve the performance of the players and teams, and subsequently enhance the continued development and sustainability of the game.

Editorial: Dimensions of knowledge-based urban development

This issue marks the beginning of a new editorial cycle. In the seventh volume of the journal the editorial team will continue collating novel scientific and social developments in the broader field of ‘knowledge-based development’ to report to our readers. In this perspective, the first issue of the volume focuses on different dimensions of knowledge-based urban development. As Gabe et al. (2012, p.1179) indicate, “[i]t would be an understatement to suggest that knowledge plays a key role in today’s economy; for much of the developed world, it might be more accurate to assert that knowledge is today’s economy”. Thus, knowledge generation has been a priority for global city administrations, and there is a growing consensus amongst scholars, planners, politicians and industrialists in identifying knowledge-based urban development as a panacea to the burgeoning economic problems (Knight, 1995; Kunzmann, 2009; Yigitcanlar, 2010, 2011; Huggins and Strakova, 2012; Lönnqvist et al., 2014). Although, in the era of global knowledge economy, knowledge-based urban development is a critical factor for economic success (Pratt, 2000; Sheppard, 2002), it is not solely an economic policy. For many, knowledge-based urban development is a policy that targets building an urban setting to form perfect climates for business, people, and governance in an environmentally friendly atmosphere (Carrillo, 2006; Ergazakis et al., 2006; Angelidou et al., 2012). Each of these climates correspond to a dimension or domain of knowledge-based urban development – namely, economy, society, space, and governance (Carrillo et al., 2014). Each paper of this issue corresponds to at least one of these domains, or policy areas.

Predicting the temporal response of seagrass meadows to dredging using Dynamic Bayesian Networks

Predicting temporal responses of ecosystems to disturbances associated with industrial activities is critical for their management and conservation. However, prediction of ecosystem responses is challenging due to the complexity and potential non-linearities stemming from interactions between system components and multiple environmental drivers. Prediction is particularly difficult for marine ecosystems due to their often highly variable and complex natures and large uncertainties surrounding their dynamic responses. Consequently, current management of such systems often rely on expert judgement and/or complex quantitative models that consider only a subset of the relevant ecological processes. Hence there exists an urgent need for the development of whole-of-systems predictive models to support decision and policy makers in managing complex marine systems in the context of industry based disturbances. This paper presents Dynamic Bayesian Networks (DBNs) for predicting the temporal response of a marine ecosystem to anthropogenic disturbances. The DBN provides a visual representation of the problem domain in terms of factors (parts of the ecosystem) and their relationships. These relationships are quantified via Conditional Probability Tables (CPTs), which estimate the variability and uncertainty in the distribution of each factor. The combination of qualitative visual and quantitative elements in a DBN facilitates the integration of a wide array of data, published and expert knowledge and other models. Such multiple sources are often essential as one single source of information is rarely sufficient to cover the diverse range of factors relevant to a management task. Here, a DBN model is developed for tropical, annual Halophila and temperate, persistent Amphibolis seagrass meadows to inform dredging management and help meet environmental guidelines. Specifically, the impacts of capital (e.g. new port development) and maintenance (e.g. maintaining channel depths in established ports) dredging is evaluated with respect to the risk of permanent loss, defined as no recovery within 5 years (Environmental Protection Agency guidelines). The model is developed using expert knowledge, existing literature, statistical models of environmental light, and experimental data. The model is then demonstrated in a case study through the analysis of a variety of dredging, environmental and seagrass ecosystem recovery scenarios. In spatial zones significantly affected by dredging, such as the zone of moderate impact, shoot density has a very high probability of being driven to zero by capital dredging due to the duration of such dredging. Here, fast growing Halophila species can recover, however, the probability of recovery depends on the presence of seed banks. On the other hand, slow growing Amphibolis meadows have a high probability of suffering permanent loss. However, in the maintenance dredging scenario, due to the shorter duration of dredging, Amphibolis is better able to resist the impacts of dredging. For both types of seagrass meadows, the probability of loss was strongly dependent on the biological and ecological status of the meadow, as well as environmental conditions post-dredging. The ability to predict the ecosystem response under cumulative, non-linear interactions across a complex ecosystem highlights the utility of DBNs for decision support and environmental management.