Minimizing overprocessing waste in business processes via predictive activity ordering

Overprocessing waste occurs in a business process when effort is spent in a way that does not add value to the customer nor to the business. Previous studies have identied a recurrent overprocessing pattern in business processes with so-called "knockout checks", meaning activities that classify a case into "accepted" or "rejected", such that if the case is accepted it proceeds forward, while if rejected, it is cancelled and all work performed in the case is considered unnecessary. Thus, when a knockout check rejects a case, the effort spent in other (previous) checks becomes overprocessing waste. Traditional process redesign methods propose to order knockout checks according to their mean effort and rejection rate. This paper presents a more fine-grained approach where knockout checks are ordered at runtime based on predictive machine learning models. Experiments on two real-life processes show that this predictive approach outperforms traditional methods while incurring minimal runtime overhead.

Multifaceted Modelling of Complex Business Enterprises

We formalise and present a new generic multifaceted complex system approach for modelling complex business enterprises. Our method has a strong focus on integrating the various data types available in an enterprise which represent the diverse perspectives of various stakeholders. We explain the challenges faced and define a novel approach to converting diverse data types into usable Bayesian probability forms. The data types that can be integrated include historic data, survey data, and management planning data, expert knowledge and incomplete data. The structural complexities of the complex system modelling process, based on various decision contexts, are also explained along with a solution. This new application of complex system models as a management tool for decision making is demonstrated using a railway transport case study. The case study demonstrates how the new approach can be utilised to develop a customised decision support model for a specific enterprise. Various decision scenarios are also provided to illustrate the versatility of the decision model at different phases of enterprise operations such as planning and control.

Embedding sustainability in a real-world context: Developing a world class early learning centre

This symposium describes what is possible when early childhood professionals work with designers to develop a vision for an exemplary early childhood centre with a focus on Education for Sustainability (EfS). The symposium provides insights into cross-disciplinary initiatives between QUT Early childhood and Design staff and students, who have worked together with the iconic Lone Pine Koala Sanctuary in Brisbane, to explore imperatives around EfS, including leadership and professionalism. This practical, real world project has seen all stakeholders engage in a focus on sustainability which has opened new ways of thinking about early childhood centre design. Cross-disciplinarity has created space to re-think the potential of the disciplines to interweave, and in so doing opened different ways for thinking about early childhood centres – their operation and their function. For the first time in Queensland, this project creates strategic alliances between EfS, childcare, business and sustainable design. EfS is essential for addressing local and global environmental issues and early childhood EfS research has been gaining international momentum, with governments nominating this area as having significant capacity to empower communities and promote change. While models for collaboration exist in the early childhood programs in Reggio Emilia, we offer sustainability as a unique and contemporary focus with immense potential to generate international and national interest. To date Early Childhood degree students enrolled in a leadership and management unit/subject have worked collaboratively with Design students to explore the sustainable design of the proposed Lone Pine early childhood centre. Providing students with a ‘real world’ project sees them re-positioned from ‘novice’ to ‘professional’, where their knowledge, expertise and perspectives are simultaneously validated and challenged. These learning experiences are enabling students to practice a new model of early childhood leadership, one that is vital for leading in an increasingly complex world. The symposium will be comprised of three discrete, though interconnected presentations, that work together to tell the story of this project. Three key facets of the project will be explored during the 90 minute session, as the perspectives of key stakeholders are shared. The first presentation (A/Prof Julie Davis, Dr Lyndal O’Gorman& Dr Megan Gibson) will outline the role of QUT School of Early Childhood staff and students, with attention to the ways in which the project was embedded in students’ work in the final year of their degree program of study. The second presentation (Ms Lindy Osborne) will provide insights into the Design students’ collaborative work in the project. Finally, the key role of the Lone Pine Koala Sanctuary and their commitment for EfS (Ms Peta Wilson & Dr Sue Elliott) will map out the philosophy that underpins the project. Together, the authors will conclude key project outcomes that have been achieved through this real-world, cross-disciplinary work.

Developing sustainable banana production systems: a case study from tropical Australia

The north Queensland banana industry is under pressure from government and community expectations to exhibit good environmental stewardship. The industry is situated on the high-rainfall north Queensland coast adjacent to 2 natural icons, the Great Barrier Reef to the east and World Heritage-listed rain forest areas to the west. The main environmental concern is agricultural industry pollutants harming the Great Barrier Reef. In addition to environmental issues the banana industry also suffers financial pressure from declining margins and production loss from tropical cyclones. As part of a broader government strategy to reduce land-based pollutants affecting the Great Barrier Reef, the formation of a pilot banana producers group to address these environmental and economic pressures was facilitated. Using an integrated farming systems approach, we worked collaboratively with these producers to conduct an environmental risk assessment of their businesses and then to develop best management practices (BMP) to address environmental concerns. We also sought input from technical experts to provide increased rigour for the environmental risk assessment and BMP development. The producers' commercial experience ensured new ideas for improved sustainable practices were constantly assessed through their profit-driven 'filter' thus ensuring economic sustainability was also considered. Relying heavily on the producers' knowledge and experience meant the agreed sustainable practices were practical, relevant and financially feasible for the average-sized banana business in the region. Expert input and review also ensured that practices were technically sound. The pilot group producers then implemented and adapted selected key practices on their farms. High priority practices addressed by the producers group included optimizing nitrogen fertilizer management to reduce runoff water nitrification, developing practical ground cover management to reduce soil erosion and improving integrated pest management systems to reduce pesticide use. To facilitate wider banana industry understanding and adoption of the BMP's developed by the pilot group, we conducted field days at the farms of the pilot group members. Information generated by the pilot group has had wider application to Australian horticulture and the process has been subsequently used with the north Queensland sugar industry. Our experiences have shown that integrated farming systems methodologies are useful in addressing complex issues like environmental and economic sustainability. We have also found that individual horticulture businesses need on-going technical support for change to more sustainable practices. One-off interventions have little impact, as farm improvement is usually an on-going incremental process. A key lesson from this project has been the need to develop practical, farm scale economic tools to clarify and demonstrate the financial impact of alternative management practices. Demonstrating continued profitability is critical to encourage widespread industry adoption of environmentally sustainable practices

Complete and interpretable conformance checking of business processes

This article presents a method for checking the conformance between an event log capturing the actual execution of a business process, and a model capturing its expected or normative execution. Given a business process model and an event log, the method returns a set of statements in natural language describing the behavior allowed by the process model but not observed in the log and vice versa. The method relies on a unified representation of process models and event logs based on a well-known model of concurrency, namely event structures. Specifically, the problem of conformance checking is approached by folding the input event log into an event structure, unfolding the process model into another event structure, and comparing the two event structures via an error-correcting synchronized product. Each behavioral difference detected in the synchronized product is then verbalized as a natural language statement. An empirical evaluation shows that the proposed method scales up to real-life datasets while producing more concise and higher-level difference descriptions than state-of-the-art conformance checking methods.

Sustainable Beef Industry Improvement and Innovation

This project ensures Queensland's involvement in Beef CRC Project 5.4 Accelerated Adoption through Sustainable Beef Profit Partnerships (BPP). The project researches, develops and achieves measurable improvements in business and industry productivity, profit and efficiency.

Central Queensland Sustainable Farming Systems - Phase 3

This project employed a participatory development and extension (D&E) approach involving on-farm trials and capacity- building activities to improve the economic and environmental performance of grain and mixed farming enterprises in central Queensland (CQ). The project's activities delivered (1) enhanced knowledge and understanding of key system variables that underpin grain and mixed farming businesses, and parameter values for these variables in relation to a range of environmental and management factors, (2) new and refined practices, technologies and management strategies to sustain the profitability of cropping and (3) products and information to support continuous improvement in farm business performance.

A multi-field bio-economic model of irrigated grain-cotton farming systems.

We present a participatory modelling framework that integrates information from interviews and discussions with farmers and consultants, with dynamic bio-economic models to answer complex questions on the allocation of limited resources at the farm business level. Interviews and discussions with farmers were used to: describe the farm business; identify relevant research questions; identify potential solutions; and discuss and learn from the whole-farm simulations. The simulations are done using a whole-farm, multi-field configuration of APSIM (APSFarm). APSFarm results were validated against farmers' experience. Once the model was accepted by the participating farmers as a fair representation of their farm business, the model was used to explore changes in the tactical or strategic management of the farm and results were then discussed to identify feasible options for improvement. Here we describe the modelling framework and present an example of the application of integrative whole farm system tools to answer relevant questions from an irrigated farm business case study near Dalby (151.27E - 27.17S), Queensland, Australia. Results indicated that even though cotton crops generates more farm income per hectare a more diversified rotation with less cotton would be relatively more profitable, with no increase in risk, as a more cotton dominated traditional rotation. Results are discussed in terms of the benefits and constraints from developing and applying more integrative approaches to represent farm businesses and their management in participatory research projects with the aim of designing more profitable and sustainable irrigated farming systems.

Debunking Weak Sustainable Consumption : Towards Strong Sustainable Consumption Governance

Achieving sustainable consumption patterns is a crucial step on the way towards sustainability. The scientific knowledge used to decide which priorities to set and how to enforce them has to converge with societal, political, and economic initiatives on various levels: from individual household decision-making to agreements and commitments in global policy processes. The aim of this thesis is to draw a comprehensive and systematic picture of sustainable consumption and to do this it develops the concept of Strong Sustainable Consumption Governance. In this concept, consumption is understood as resource consumption. This includes consumption by industries, public consumption, and household consumption. Next to the availability of resources (including the available sink capacity of the ecosystem) and their use and distribution among the Earth’s population, the thesis also considers their contribution to human well-being. This implies giving specific attention to the levels and patterns of consumption. Methods: The thesis introduces the terminology and various concepts of Sustainable Consumption and of Governance. It briefly elaborates on the methodology of Critical Realism and its potential for analysing Sustainable Consumption. It describes the various methods on which the research is based and sets out the political implications a governance approach towards Strong Sustainable Consumption may have. Two models are developed: one for the assessment of the environmental relevance of consumption activities, another to identify the influences of globalisation on the determinants of consumption opportunities. Results: One of the major challenges for Strong Sustainable Consumption is that it is not in line with the current political mainstream: that is, the belief that economic growth can cure all our problems. So, the proponents have to battle against a strong headwind. Their motivation however is the conviction that there is no alternative. Efforts have to be taken on multiple levels by multiple actors. And all of them are needed as they constitute the individual strings that together make up the rope. However, everyone must ensure that they are pulling in the same direction. It might be useful to apply a carrot and stick strategy to stimulate public debate. The stick in this case is to create a sense of urgency. The carrot would be to articulate better the message to the public that a shrinking of the economy is not as much of a disaster as mainstream economics tends to suggest. In parallel to this it is necessary to demand that governments take responsibility for governance. The dominant strategy is still information provision. But there is ample evidence that hard policies like regulatory instruments and economic instruments are most effective. As for Civil Society Organizations it is recommended that they overcome the habit of promoting Sustainable (in fact green) Consumption by using marketing strategies and instead foster public debate in values and well-being. This includes appreciating the potential of social innovation. A countless number of such initiatives are on the way but their potential is still insufficiently explored. Beyond the question of how to multiply such approaches, it is also necessary to establish political macro structures to foster them.

Sustainable building envelope design by considering energy cost and occupant satisfaction

The built environment is a major contributor to the world’s carbon dioxide emissions, with a considerable amount of energy being consumed in buildings due to heating, ventilation and air-conditioning, space illumination, use of electrical appliances, etc., to facilitate various anthropogenic activities. The development of sustainable buildings seeks to ameliorate this situation mainly by reducing energy consumption. Sustainable building design, however, is a complicated process involving a large number of design variables, each with a range of feasible values. There are also multiple, often conflicting, objectives involved such as the life cycle costs and occupant satisfaction. One approach to dealing with this is through the use of optimization models. In this paper, a new multi-objective optimization model is developed for sustainable building design by considering the design objectives of cost and energy consumption minimization and occupant comfort level maximization. In a case study demonstration, it is shown that the model can derive a set of suitable design solutions in terms of life cycle cost, energy consumption and indoor environmental quality so as to help the client and design team gain a better understanding of the design space and trade-off patterns between different design objectives. The model can very useful in the conceptual design stages to determine appropriate operational settings to achieve the optimal building performance in terms of minimizing energy consumption and maximizing occupant comfort level.

Automated Discovery of Structured Process Models: Discover Structured vs. Discover and Structure

This paper addresses the problem of discovering business process models from event logs. Existing approaches to this problem strike various tradeoffs between accuracy and understandability of the discovered models. With respect to the second criterion, empirical studies have shown that block-structured process models are generally more understandable and less error-prone than unstructured ones. Accordingly, several automated process discovery methods generate block-structured models by construction. These approaches however intertwine the concern of producing accurate models with that of ensuring their structuredness, sometimes sacrificing the former to ensure the latter. In this paper we propose an alternative approach that separates these two concerns. Instead of directly discovering a structured process model, we first apply a well-known heuristic technique that discovers more accurate but sometimes unstructured (and even unsound) process models, and then transform the resulting model into a structured one. An experimental evaluation shows that our “discover and structure” approach outperforms traditional “discover structured” approaches with respect to a range of accuracy and complexity measures.

How to measure sustainable progress

In September, the United Nations General Assembly adopted Sustainable Development Goals (SDGs), to be met by the year 2030. These important goals range from poverty eradication and improvements in education and health to the protection of global assets, including the oceans and a stable climate. Unfortunately, neither the SDGs nor their background documents explain how governments should judge whether the development programs they undertake to meet the goals are sustainable.

How small business managers’ age and focus on opportunities affect business growth: A mediated moderation growth model

Research on business growth has been criticized for methodological weaknesses. We present a mediated moderation growth model as a new methodological approach. We hypothesized that small business managers' age negatively affects business growth through focus on opportunities. We sampled 201 small business managers and obtained firm performance data over 5 years, resulting in 836 observations. Growth modeling showed systematic differences in firm performance trajectories. These differences could be explained by modeling focus on opportunities as a mediator of the relationship between small business managers' age and business growth. The study illustrates how mediation models can be tested using growth modeling.

Studies on Binary Time Series Models with Applications to Empirical Macroeconomics and Finance

This thesis studies binary time series models and their applications in empirical macroeconomics and finance. In addition to previously suggested models, new dynamic extensions are proposed to the static probit model commonly used in the previous literature. In particular, we are interested in probit models with an autoregressive model structure. In Chapter 2, the main objective is to compare the predictive performance of the static and dynamic probit models in forecasting the U.S. and German business cycle recession periods. Financial variables, such as interest rates and stock market returns, are used as predictive variables. The empirical results suggest that the recession periods are predictable and dynamic probit models, especially models with the autoregressive structure, outperform the static model. Chapter 3 proposes a Lagrange Multiplier (LM) test for the usefulness of the autoregressive structure of the probit model. The finite sample properties of the LM test are considered with simulation experiments. Results indicate that the two alternative LM test statistics have reasonable size and power in large samples. In small samples, a parametric bootstrap method is suggested to obtain approximately correct size. In Chapter 4, the predictive power of dynamic probit models in predicting the direction of stock market returns are examined. The novel idea is to use recession forecast (see Chapter 2) as a predictor of the stock return sign. The evidence suggests that the signs of the U.S. excess stock returns over the risk-free return are predictable both in and out of sample. The new "error correction" probit model yields the best forecasts and it also outperforms other predictive models, such as ARMAX models, in terms of statistical and economic goodness-of-fit measures. Chapter 5 generalizes the analysis of univariate models considered in Chapters 2 4 to the case of a bivariate model. A new bivariate autoregressive probit model is applied to predict the current state of the U.S. business cycle and growth rate cycle periods. Evidence of predictability of both cycle indicators is obtained and the bivariate model is found to outperform the univariate models in terms of predictive power.

Commercialization of sustainable energy technologies

Commercialization efforts to diffuse sustainable energy technologies (SETs1) have so far remained as the biggest challenge in the field of renewable energy and energy efficiency. Limited success of diffusion through government driven pathways urges the need for market based approaches. This paper reviews the existing state of commercialization of SETs in the backdrop of the basic theory of technology diffusion. The different SETs in India are positioned in the technology diffusion map to reflect their slow state of commercialization. The dynamics of SET market is analysed to identify the issues, barriers and stakeholders in the process of SET commercialization. By upgrading the ‘potential adopters’ to ‘techno-entrepreneurs’, the study presents the mechanisms for adopting a private sector driven ‘business model’ approach for successful diffusion of SETs. This is expected to integrate the processes of market transformation and entrepreneurship development with innovative regulatory, marketing, financing, incentive and delivery mechanisms leading to SET commercialization.