Foundations for giving : why and how Australians structure their philanthropy

Philanthropic foundations in Australia have traditionally been labelled ‘icebergs’. Much of what they do and who they are is not apparent on the surface. Many are unknown and apart from an occasional biography, almost all are sparsely documented in terms of the very personal decisions behind establishing them. Practically and academically, scant data exist on the decision journeys people make into formalised philanthropy. This study seeks to fill that gap. It is believed to be the largest such study of foundation decision-making ever undertaken in this country. It is the latest in a series of ACPNS research into types of considered (versus spontaneous) giving in Australia. This research has been supported by the Perpetual Foundation, the EF and SL Gluyas Trust and the Edward Corbould Charitable Trust under the management of Perpetual Trustee Company Ltd.

Complex events in business processes

Flow-oriented process modeling languages have a long tradition in the area of Business Process Management and are widely used for capturing activities with their behavioral and data dependencies. Individual events were introduced for triggering process instantiation and activities. However, real-world business cases drive the need for also covering complex event patterns as they are known in the field of Complex Event Processing. Therefore, this paper puts forward a catalog of requirements for handling complex events in process models, which can be used as reference framework for assessing process definition languages and systems. An assessment of BPEL and BPMN is provided.

Integration of opinion into customer analysis model

Nowadays, Opinion Mining is getting more important than before especially in doing analysis and forecasting about customers’ behavior for businesses purpose. The right decision in producing new products or services based on data about customers’ characteristics means profit for organization/company. This paper proposes a new architecture for Opinion Mining, which uses a multidimensional model to integrate customers’ characteristics and their comments about products (or services). The key step to achieve this objective is to transfer comments (opinions) to a fact table that includes several dimensions, such as, customers, products, time and locations. This research presents a comprehensive way to calculate customers’ orientation for all possible products’ attributes. A use case study is also presented in this paper to show the advantages of using OLAP and data cubes to analyze costumers’ opinions.

Approximate clone detection in repositories of business process models

Evidence exists that repositories of business process models used in industrial practice contain significant amounts of duplication. This duplication may stem from the fact that the repository describes variants of the same pro- cesses and/or because of copy/pasting activity throughout the lifetime of the repository. Previous work has put forward techniques for identifying duplicate fragments (clones) that can be refactored into shared subprocesses. However, these techniques are limited to finding exact clones. This paper analyzes the prob- lem of approximate clone detection and puts forward two techniques for detecting clusters of approximate clones. Experiments show that the proposed techniques are able to accurately retrieve clusters of approximate clones that originate from copy/pasting followed by independent modifications to the copied fragments.

A Business Continuity Management Simulator

Comprehensive BCM plan testing for complex information systems is difficult and expensive, if not infeasible. This paper suggests that a simulator could be employed to ameliorate these problems. A general model for such a BCM simulator is presented, and the implementation of a prototype simulator is described. The simulator reacts to system disturbances by seeking alternative configurations provided within the BCM plan, reporting the resource availabilities in the updated system and identifying any failure to meet the requirements placed on the system. The simulator then explores any changes in data security introduced by the proposed post disturbance configuration and reports any enhanced risk.

A requirements framework for semantic business process modelling

The emergence of semantic technologies to deal with the underlying meaning of things, instead of a purely syntactical representation, has led to new developments in various fields, including business process modeling. Inspired by artificial intelligence research, technologies for semantic Web services have been proposed and extended to process modeling. However, the applicablility of semantic Web services for semantic business processes is limited because business processes encompass wider requirements of business than Web services. In particular, processes are concerned with the composition of tasks, that is, in which order activities are carried out, regardless of their implementation details; resources assigned to carry out tasks, such as machinery, people, and goods; data exchange; and security and compliance concerns.

Sourcing and evaluating IT business value in emerging economies : the case of the South Pacific Island Countries

Information Technology (IT) is an important resource that facilitates growth and development in both the developed and emerging economies. The increasing forces of globalization are creating a wider digital divide between the developed and emerging economies. The smaller emerging economies are the most venerable. Intense competition for IT resources means that these emerging economies would need to acquire a deeper understanding of how to source and evaluate their IT-related efforts. This effort would put these economies in a better position to source funding from various stakeholders. This research presents a complementary approach to securing better IT-related business value in organizations in the South Pacific Island countries – a case of emerging economies. Analysis of data collected from six South Pacific Island countries suggests that organizations that invest in IT and related complementaries are able to better their business processes. The data also suggest that improved business processes lead to overall business processes improvements.

ACE research briefing paper 002: learning and adaptation in the business creation process

This year marks the completion of data collection for year three (Wave 3) of the CAUSEE study. This report uses data from the first three years and focuses on the process of learning and adaptation in the business creation process. Most start-ups need to change their business model, their product, their marketing plan, their market or something else about the business to be successful. PayPal changed their product at least five times, moving from handheld security, to enterprise apps, to consumer apps, to a digital wallet, to payments between handhelds before finally stumbling on the model that made the a multi-billion dollar company revolving around email-based payments. PayPal is not alone and anecdotes abounds of start-ups changing direction: Sysmantec started as an artificial intelligence company, Apple started selling plans to build computers and Microsoft tried to peddle compilers before licensing an operating system out of New Mexico. To what extent do Australian new ventures change and adapt as their ideas and business develop? As a longitudinal study, CAUSEE was designed specifically to observe development in the venture creation process. In this research briefing paper, we compare development over time of randomly sampled Nascent Firms (NF) and Young Firms(YF), concentrating on the surviving cases. We also compare NFs with YFs at each yearly interval. The 'high potential' over sample is not used in this report.

Toward resolving deep neoaves phylogeny : data, signal enhancement, and priors

We report three developments toward resolving the challenge of the apparent basal polytomy of neoavian birds. First, we describe improved conditional down-weighting techniques to reduce noise relative to signal for deeper divergences and find increased agreement between data sets. Second, we present formulae for calculating the probabilities of finding predefined groupings in the optimal tree. Finally, we report a significant increase in data: nine new mitochondrial (mt) genomes (the dollarbird, New Zealand kingfisher, great potoo, Australian owlet-nightjar, white-tailed trogon, barn owl, a roadrunner [a ground cuckoo], New Zealand long-tailed cuckoo, and the peach-faced lovebird) and together they provide data for each of the six main groups of Neoaves proposed by Cracraft J (2001). We use his six main groups of modern birds as priors for evaluation of results. These include passerines, cuckoos, parrots, and three other groups termed “WoodKing” (woodpeckers/rollers/kingfishers), “SCA” (owls/potoos/owlet-nightjars/hummingbirds/swifts), and “Conglomerati.” In general, the support is highly significant with just two exceptions, the owls move from the “SCA” group to the raptors, particularly accipitrids (buzzards/eagles) and the osprey, and the shorebirds may be an independent group from the rest of the “Conglomerati”. Molecular dating mt genomes support a major diversification of at least 12 neoavian lineages in the Late Cretaceous. Our results form a basis for further testing with both nuclear-coding sequences and rare genomic changes.

Meeting under the “Omei” Tree in the Torres Strait Islands : networks and funds of knowledge of mathematical ideas

This paper focuses on the turning point experiences that worked to transform the researcher during a preliminary consultation process to seek permission to conduct of a small pilot project on one Torres Strait Island. The project aimed to learn from parents how they support their children in their mathematics learning. Drawing on a community research design, a consultative meeting was held with one Torres Strait Islander community to discuss the possibility of piloting a small project that focused on working with parents and children to learn about early mathematics processes. Preliminary data indicated that parents use networks in their community. It highlighted the funds of knowledge of mathematics that exist in the community and which are used to teach their children. Such knowledges are situated within a community’s unique histories, culture and the voices of the people. “Omei” tree means the Tree of Wisdom in the Island community.

Effects of Mobile Phone Distraction at the Onset of Amber Light: Analysis of Driving Simulator Data

Distraction whilst driving on an approach to a signalized intersection is particularly dangerous, as potential vehicular conflicts and resulting angle collisions tend to be severe. This study examines the decisions of distracted drivers during the onset of amber lights. Driving simulator data were obtained from a sample of 58 drivers under baseline and handheld mobile phone conditions at the University of IOWA - National Advanced Driving Simulator. Explanatory variables include age, gender, cell phone use, distance to stop-line, and speed. An iterative combination of decision tree and logistic regression analyses are employed to identify main effects, non-linearities, and interactions effects. Results show that novice (16-17 years) and younger (18-25 years) drivers’ had heightened amber light running risk while distracted by cell phone, and speed and distance thresholds yielded significant interaction effects. Driver experience captured by age has a multiplicative effect with distraction, making the combined effect of being inexperienced and distracted particularly risky. Solutions are needed to combat the use of mobile phones whilst driving.

Leveraging social network data for analytical CRM strategies : the introduction of social BI

The skyrocketing trend for social media on the Internet greatly alters analytical Customer Relationship Management (CRM). Against this backdrop, the purpose of this paper is to advance the conceptual design of Business Intelligence (BI) systems with data identified from social networks. We develop an integrated social network data model, based on an in-depth analysis of Facebook. The data model can inform the design of data warehouses in order to offer new opportunities for CRM analyses, leading to a more consistent and richer picture of customers? characteristics, needs, wants, and demands. Four major contributions are offered. First, Social CRM and Social BI are introduced as emerging fields of research. Second, we develop a conceptual data model to identify and systematize the data available on online social networks. Third, based on the identified data, we design a multidimensional data model as an early contribution to the conceptual design of Social BI systems and demonstrate its application by developing management reports in a retail scenario. Fourth, intellectual challenges for advancing Social CRM and Social BI are discussed.

Learning in and beyond small business advisory programmes

The purpose of this paper is to analyse how participants learn in small business advisory programmes and to explore the impact of these learning programmes on the development of reflective learning dispositions in participants. The research involves two case studies of small business advisory programmes in Queensland, a state of Australia. One involves training in the use of GPS/GIS technology amongst rural SMEs and the other seeks to develop improved management and operational capabilities in regional and metropolitan manufacturing SMEs. Face to face semi-structured interviews were conducted throughout rural, regional and metropolitan Queensland with participants, trainers and senior executives in the administering organisations that ran the programmes. Learning in these programmes occurs through a combination of interaction with others and the adoption of practice-based and learner-centred processes. The impact of the programmes on participants includes the development of reflective learning dispositions, improved confidence in learning and appreciation of the value of new knowledge to their business. The research suggests that small business training programmes have the potential to affect the development of critical reflective learning dispositions in participants which is of fundamental importance to the development of a learning or knowledge economy.

Analysing and improving a recruitment process : a teaching case for developing business process improvement capabilities

The demand for Business Process Management (BPM) is rapidly rising and with that, the need for capable BPM professionals is also rising. Yet, only a very few structured BPM training/ education programs are available, across universities and professional trainers globally. The ‘lack of appropriate teaching resources’ has been identified as a critical issue for BPM educators in prior studies. Case-based teaching can be an effective means of educating future BPM professionals. A main reason is that cases create an authentic learning environment where the complexities and challenges of the ‘real world’ can be presented in a narrative enabling the students to develop crucial skills such as problem solving, analysis and creativity-within-constraints, and to apply the tools and techniques within a richer and real (or proxy to real) context. However, so far well documented BPM teaching cases are scarce. This article aims to contribute to address this gap by providing a comprehensive teaching case and teaching notes that facilitates the education of selected process improvement phases, namely identification, modelling, analysis, and improvement. The article is divided into three main parts: (i) Introductory teaching notes, (ii) The case narrative, and (iii) Student activities from the case and teaching notes.