The importance of considering social issues in reforestation schemes

This paper reports the results of a survey of north Queensland landholder attitudes with respect to a number of issues relating to participation in forestry. The survey explored the reasons why landholders plant trees, perceived obstacles to greater farm forestry, and attitudes to tree planting programs such as the Community Rainforest Reforestation Program (CRRP) and Private Joint Venture Scheme (PJVS). The results of the survey are discussed in the context of possible policy prescriptions that can be made at local, state and federal government levels to facilitate greater tree planting in the region. Many of the problems faced by local landholders are shared by landholders in other parts of Australia and throughout the world. This survey can thus serve as a case study, providing information on a number of issues concerning small-scale forestry policies that are of general relevance to the development of farm forestry programs.

Major issues in business process management: An Australian perspective

Business Process Management (BPM) is widely seen as the top priority in organizations wanting to survive competitive markets. However, the current academic research agenda does not seem to map with industry demands. In this paper, we address the need to identify the actual issues that organizations face in their efforts to manage business processes. To that end, we report a number of critical issues identified by industry in what we consider to be the first steps towards an industry-driven research agenda for the BPM area. The reported issues are derived from a series of focus groups conducted with Australian organizations. The findings point to, among others, a need for more consolidated efforts in the areas of business process governance, systematic change management, developing BPM methodologies, and introducing appropriate performance measures.

A framework of issues in large process modeling projects

As process management projects have increased in size due to globalised and company-wide initiatives, a corresponding growth in the size of process modeling projects can be observed. Despite advances in languages, tools and methodologies, several aspects of these projects have been largely ignored by the academic community. This paper makes a first contribution to a potential research agenda in this field by defining the characteristics of large-scale process modeling projects and proposing a framework of related issues. These issues are derived from a semi -structured interview and six focus groups conducted in Australia, Germany and the USA with enterprise and modeling software vendors and customers. The focus groups confirm the existence of unresolved problems in business process modeling projects. The outcomes provide a research agenda which directs researchers into further studies in global process management, process model decomposition and the overall governance of process modeling projects. It is expected that this research agenda will provide guidance to researchers and practitioners by focusing on areas of high theoretical and practical relevance.

On aggregation issues in spatial data management

Large amounts of information can be overwhelming and costly to process, especially when transmitting data over a network. A typical modern Geographical Information System (GIS) brings all types of data together based on the geographic component of the data and provides simple point-and-click query capabilities as well as complex analysis tools. Querying a Geographical Information System, however, can be prohibitively expensive due to the large amounts of data which may need to be processed. Since the use of GIS technology has grown dramatically in the past few years, there is now a need more than ever, to provide users with the fastest and least expensive query capabilities, especially since an approximated 80 % of data stored in corporate databases has a geographical component. However, not every application requires the same, high quality data for its processing. In this paper we address the issues of reducing the cost and response time of GIS queries by preaggregating data by compromising the data accuracy and precision. We present computational issues in generation of multi-level resolutions of spatial data and show that the problem of finding the best approximation for the given region and a real value function on this region, under a predictable error, in general is "NP-complete.