Thresholds for error probability measures of business process models

The quality of conceptual business process models is highly relevant for the design of corresponding information systems. In particular, a precise measurement of model characteristics can be beneficial from a business perspective, helping to save costs thanks to early error detection. This is just as true from a software engineering point of view. In this latter case, models facilitate stakeholder communication and software system design. Research has investigated several proposals as regards measures for business process models, from a rather correlational perspective. This is helpful for understanding, for example size and complexity as general driving forces of error probability. Yet, design decisions usually have to build on thresholds, which can reliably indicate that a certain counter-action has to be taken. This cannot be achieved only by providing measures; it requires a systematic identification of effective and meaningful thresholds. In this paper, we derive thresholds for a set of structural measures for predicting errors in conceptual process models. To this end, we use a collection of 2,000 business process models from practice as a means of determining thresholds, applying an adaptation of the ROC curves method. Furthermore, an extensive validation of the derived thresholds was conducted by using 429 EPC models from an Australian financial institution. Finally, significant thresholds were adapted to refine existing modeling guidelines in a quantitative way.

Fundamentals of process integration

Technologies and languages for integrated processes are a relatively recent innovation. Over that period many divergent waves of innovation have transformed process integration. Like sockets and distributed objects, early workflow systems ordered programming interfaces that connected the process modelling layer to any middleware. BPM systems emerged later, connecting the modelling world to middleware through components. While BPM systems increased ease of use (modelling convenience), long-standing and complex interactions involving many process instances remained di±cult to model. Enterprise Service Buses (ESBs), followed, connecting process models to heterogeneous forms of middleware. ESBs, however, generally forced modellers to choose a particular underlying middleware and to stick to it, despite their ability to connect with many forms of middleware. Furthermore ESBs encourage process integrations to be modelled on their own, logically separate from the process model. This can lead to the inability to reason about long standing conversations at the process layer. Technologies and languages for process integration generally lack formality. This has led to arbitrariness in the underlying language building blocks. Conceptual holes exist in a range of technologies and languages for process integration and this can lead to customer dissatisfaction and failure to bring integration projects to reach their potential. Standards for process integration share similar fundamental flaws to languages and technologies. Standards are also in direct competition with other standards causing a lack of clarity. Thus the area of greatest risk in a BPM project remains process integration, despite major advancements in the technology base. This research examines some fundamental aspects of communication middleware and how these fundamental building blocks of integration can be brought to the process modelling layer in a technology agnostic manner. This way process modelling can be conceptually complete without becoming stuck in a particular middleware technology. Coloured Petri nets are used to define a formal semantics for the fundamental aspects of communication middleware. They provide the means to define and model the dynamic aspects of various integration middleware. Process integration patterns are used as a tool to codify common problems to be solved. Object Role Modelling is a formal modelling technique that was used to define the syntax of a proposed process integration language. This thesis provides several contributions to the field of process integration. It proposes a framework defining the key notions of integration middleware. This framework provides a conceptual foundation upon which a process integration language could be built. The thesis defines an architecture that allows various forms of middleware to be aggregated and reasoned about at the process layer. This thesis provides a comprehensive set of process integration patterns. These constitute a benchmark for the kinds of problems a process integration language must support. The thesis proposes a process integration modelling language and a partial implementation that is able to enact the language. A process integration pilot project in a German hospital is brie°y described at the end of the thesis. The pilot is based on ideas in this thesis.

Tracking the defining moments of crisis process and practice

Crisis holds the potential for profound change in organizations and industries. The past 50 years of crisis management highlight key shifts in crisis practice, creating opportunities for multiple theories and research tracks. Defining crises such as Tylenol, Exxon Valdez, and September 11 terrorist attacks have influenced or challenged the principles of best practice of crisis communication in public relations. This study traces the development of crisis process and practice by identifying shifts in crisis research and models and mapping these against key management theories and practices. The findings define three crisis domains: crisis planning, building and testing predictive models, and mapping and measuring external environmental influences. These crisis domains mirror but lag the evolution of management theory, suggesting challenges for researchers to reshape the research agenda to close the gap and lead the next stage of development in the field of crisis communication for effective organizational outcomes.

Introduction to the First International Workshop on Empirical Research in Business Process Management (ER-BPM 2009)

Providing effective IT support for business processes has become crucial for enterprises to stay competitive. In response to this need numerous process support paradigms (e.g., workflow management, service flow management, case handling), process specification standards (e.g., WS-BPEL, BPML, BPMN), process tools (e.g., ARIS Toolset, Tibco Staffware, FLOWer), and supporting methods have emerged in recent years. Summarized under the term “Business Process Management” (BPM), these paradigms, standards, tools, and methods have become a success-critical instrument for improving process performance.

Managing large collections of business process models - Current techniques and challenges

Nowadays, business process management is an important approach for managing organizations from an operational perspective. As a consequence, it is common to see organizations develop collections of hundreds or even thousands of business process models. Such large collections of process models bring new challenges and provide new opportunities, as the knowledge that they encapsulate requires to be properly managed. Therefore, a variety of techniques for managing large collections of business process models is being developed. The goal of this paper is to provide an overview of the management techniques that currently exist, as well as the open research challenges that they pose.

Thermal profile of a near-adiabatic compression process in a cylindrical tube and establishment of critical control elements for repeatable process control

The compressed gas industry and government agencies worldwide utilize "adiabatic compression" testing for qualifying high-pressure valves, regulators, and other related flow control equipment for gaseous oxygen service. This test methodology is known by various terms including adiabatic compression testing, gaseous fluid impact testing, pneumatic impact testing, and BAM testing as the most common terms. The test methodology will be described in greater detail throughout this document but in summary it consists of pressurizing a test article (valve, regulator, etc.) with gaseous oxygen within 15 to 20 milliseconds (ms). Because the driven gas1 and the driving gas2 are rapidly compressed to the final test pressure at the inlet of the test article, they are rapidly heated by the sudden increase in pressure to sufficient temperatures (thermal energies) to sometimes result in ignition of the nonmetallic materials (seals and seats) used within the test article. In general, the more rapid the compression process the more "adiabatic" the pressure surge is presumed to be and the more like an isentropic process the pressure surge has been argued to simulate. Generally speaking, adiabatic compression is widely considered the most efficient ignition mechanism for directly kindling a nonmetallic material in gaseous oxygen and has been implicated in many fire investigations. Because of the ease of ignition of many nonmetallic materials by this heating mechanism, many industry standards prescribe this testing. However, the results between various laboratories conducting the testing have not always been consistent. Research into the test method indicated that the thermal profile achieved (i.e., temperature/time history of the gas) during adiabatic compression testing as required by the prevailing industry standards has not been fully modeled or empirically verified, although attempts have been made. This research evaluated the following questions: 1) Can the rapid compression process required by the industry standards be thermodynamically and fluid dynamically modeled so that predictions of the thermal profiles be made, 2) Can the thermal profiles produced by the rapid compression process be measured in order to validate the thermodynamic and fluid dynamic models; and, estimate the severity of the test, and, 3) Can controlling parameters be recommended so that new guidelines may be established for the industry standards to resolve inconsistencies between various test laboratories conducting tests according to the present standards?

Gaussian process models for sensor-centric robot localisation

This paper presents an approach to building an observation likelihood function from a set of sparse, noisy training observations taken from known locations by a sensor with no obvious geometric model. The basic approach is to fit an interpolant to the training data, representing the expected observation, and to assume additive sensor noise. This paper takes a Bayesian view of the problem, maintaining a posterior over interpolants rather than simply the maximum-likelihood interpolant, giving a measure of uncertainty in the map at any point. This is done using a Gaussian process framework. To validate the approach experimentally, a model of an environment is built using observations from an omni-directional camera. After a model has been built from the training data, a particle filter is used to localise while traversing this environment

The development of a conceptual framework for a district 4-Year Pavement Management Plan, implementation of network-level project screening process

The Texas Department of Transportation (TxDOT) is concerned about the widening gap between preservation needs and available funding. Funding levels are not adequate to meet the preservation needs of the roadway network; therefore projects listed in the 4-Year Pavement Management Plan must be ranked to determine which projects should be funded now and which can be postponed until a later year. Currently, each district uses locally developed methods to prioritize projects. These ranking methods have relied on less formal qualitative assessments based on engineers’ subjective judgment. It is important for TxDOT to have a 4-Year Pavement Management Plan that uses a transparent, rational project ranking process. The objective of this study is to develop a conceptual framework that describes the development of the 4-Year Pavement Management Plan. It can be largely divided into three Steps; 1) Network-Level project screening process, 2) Project-Level project ranking process, and 3) Economic Analysis. A rational pavement management procedure and a project ranking method accepted by districts and the TxDOT administration will maximize efficiency in budget allocations and will potentially help improve pavement condition. As a part of the implementation of the 4-Year Pavement Management Plan, the Network-Level Project Screening (NLPS) tool including the candidate project identification algorithm and the preliminary project ranking matrix was developed. The NLPS has been used by the Austin District Pavement Engineer (DPE) to evaluate PMIS (Pavement Management Information System) data and to prepare a preliminary list of candidate projects for further evaluation.

A process evaluation of a comprehensive school based injury prevention program

A process evaluation enables understanding of critical issues that can inform the improved, ongoing implementation of an intervention program. This study describes the process evaluation of a comprehensive, multi-level injury prevention program for adolescents. The program targets change in injury associated with violence, transport and alcohol risks and incorporates two primary elements: an 8-week, teacher delivered attitude and behaviour change curriculum for Grade 8 students; and a professional development program for teachers on school level methods of protection, focusing on strategies to increase students’ connectedness to school.

A sequence analytic model of entrepreneurial discovery and exploitation process

This study examined the effect that temporal order within the entrepreneurial discovery exploitation process has on the outcomes of venture creation. Consistent with sequential theories of discovery-exploitation, the general flow of venture creation was found to be directed from discovery toward exploitation in a random sample of nascent ventures. However, venture creation attempts which specifically follow this sequence derive poor outcomes. Moreover, simultaneous discovery-exploitation was the most prevalent temporal order observed, and venture attempts that proceed in this manner more likely become operational. These findings suggest that venture creation is a multi-scale phenomenon that is at once directional in time, and simultaneously driven by symbiotically coupled discovery and exploitation.

Do balanced skills help nascent entrepreneurs to make progress in the venture creation process?

We apply Lazear’s jack-of-all-trades theory to investigate the effect of nascent entrepreneurs´ balanced skill set across various functional areas on the performance of nascent projects. Analyzing longitudinal data on innovative nascent projects, we find that nascent entrepreneurs with a more balanced skill set are more successful in that they progress faster in the venture creation process.

Context-aware methods for process modeling

Recent studies have started to explore context-awareness as a driver in the design of adaptable business processes. The emerging challenge of identifying and considering contextual drivers in the environment of a business process are well understood, however, typical methods used in business process modeling do not yet consider this additional contextual information in their process designs. In this chapter, we describe our research towards innovative and advanced process modeling methods that include mechanisms to incorporate relevant contextual drivers and their impacts on business processes in process design models. We report on our ongoing work with an Australian insurance provider and describe the design science we employed to develop these innovative and useful artifacts as part of a context-aware method framework. We discuss the utility of these artifacts in an application in the claims handling process at the case organization.

Research process management

Though the value of a process-centred view for the understanding and (re-)design of corporations has been widely accepted, our understanding of the research process in Information Systems (IS) remains superficial. A process-centred view on IS research considers the conduct of a research project as a sequence of activities involving resources, data and research artifacts. As such, it helps to reflect on more effective ways to conduct IS research, to consolidate and compare diverse practices and to complement the focus on research methodologies with research project practices. This paper takes a first step towards the discipline of ‘Research Process Management’ by exploring the features of research processes and by presenting a preliminary approach for research process design that can facilitate modelling IS research. The case study method and the design science research method are used as examples to demonstrate the potential of such reference research process models.

The internetalisation of information, knowledge and interaction components of the firm’s internationalisation process

Transcending traditional national borders, the Internet is an evolving technology that has opened up many new international market opportunities. However, ambiguity remains, with limited research and understanding of how the Internet influences the firm’s internationalisation process components. As a consequence, there has been a call for further investigation of the phenomenon. Thus, the purpose of this study was to investigate the Internet’s impact on the internationalisation process components, specifically, information availability, information usage, interactive communication and international market growth. Analysis was undertaken using structural equation modelling. Findings highlight the mediating impact of the Internet on information and knowledge transference in the internationalisation process. Contributions of the study test conceptualisations and give statistical validation of interrelationships, while illuminating the Internet’s impact on firm internationalisation.

A Bayesian‐Markov process for reliability prediction

Accurate reliability prediction for large-scale, long lived engineering is a crucial foundation for effective asset risk management and optimal maintenance decision making. However, a lack of failure data for assets that fail infrequently, and changing operational conditions over long periods of time, make accurate reliability prediction for such assets very challenging. To address this issue, we present a Bayesian-Marko best approach to reliability prediction using prior knowledge and condition monitoring data. In this approach, the Bayesian theory is used to incorporate prior information about failure probabilities and current information about asset health to make statistical inferences, while Markov chains are used to update and predict the health of assets based on condition monitoring data. The prior information can be supplied by domain experts, extracted from previous comparable cases or derived from basic engineering principles. Our approach differs from existing hybrid Bayesian models which are normally used to update the parameter estimation of a given distribution such as the Weibull-Bayesian distribution or the transition probabilities of a Markov chain. Instead, our new approach can be used to update predictions of failure probabilities when failure data are sparse or nonexistent, as is often the case for large-scale long-lived engineering assets.