The social shaping of packaged software selection

As organisations increasingly engage in the selection, purchase, and adoption of packaged software products, how these activities are carried out in practice becomes increasingly relevant for researchers and practitioners. Our focus in this paper is to propose a framework for understanding the packaged software selection process. The functionalist literature on this area of study suggests a number of generic recommendations, which are based on rational assumptions about the process and view the decision making that takes place as producing the “best technology solution.’” To explore this, we conducted a longitudinal, in-depth study of packaged software selection in a small organisation. For interpretation of the case, we draw upon the Social Construction of Technology, a theoretical framework arguing that technology is socially constituted and regarding the process of development as contradictory and uncertain. We offer a number of contributions. First, we further our understanding of packaged software selection with the critique that we offer of the functionalist literature, drawing insights from the emerging critical/constructivist literature and expanding our domain of interest to encompass the wider environment. Second, we weave this together with our experiences in the field, drawing on social constructivism for theoretical support, to develop a framework of packaged software selection that shows how various actors shape the process.

CRM packaged software : a study of organisational experiences

Customer Relationship Management (CRM) packaged software has become a key contributor to attempts at aligning business and IT strategies in recent years. Throughout the 1990s there was, in many organisations strategies, a shift from the need to manage transactions and toward relationship management. Where Enterprise Resource Planning packages dominated the management of transactions era, CRM packages lead in regard to relationships. At present, balanced views of CRM packages are scantly presented instead relying on vendor rhetoric. This paper uses case study research to analyse some of the issues associated with CRM packages. These issues include the limitations of CRM packages, the need for a relationship orientation and the problems of a dominant management perspective of CRM. It is suggested that these issues could be more readily accommodated by organisational detachment from beliefs in IT as utopia, consideration of prior IS theory and practice and a more informed approach to CRM package selection.

Managing knowledge for asset management : shifting from process to relational frames

The purpose of this paper is to review existing knowledge management (KM) practices within the field of asset management, identify gaps, and propose a new approach to managing knowledge for asset management. Existing approaches to KM in the field of asset management are incomplete with the focus primarily on the application of data and information systems, for example the use of an asset register. It is contended these approaches provide access to explicit knowledge and overlook the importance of tacit knowledge acquisition, sharing and application. In doing so, current KM approaches within asset management tend to neglect the significance of relational factors; whereas studies in the knowledge management field have showed that relational modes such as social capital is imperative for ef-fective KM outcomes. In this paper, we argue that incorporating a relational ap-proach to KM is more likely to contribute to the exchange of ideas and the devel-opment of creative responses necessary to improve decision-making in asset management. This conceptual paper uses extant literature to explain knowledge management antecedents and explore its outcomes in the context of asset man-agement. KM is a component in the new Integrated Strategic Asset Management (ISAM) framework developed in conjunction with asset management industry as-sociations (AAMCoG, 2012) that improves asset management performance. In this paper we use Nahapiet and Ghoshal’s (1998) model to explain antecedents of relational approach to knowledge management. Further, we develop an argument that relational knowledge management is likely to contribute to the improvement of the ISAM framework components, such as Organisational Strategic Manage-ment, Service Planning and Delivery. The main contribution of the paper is a novel and robust approach to managing knowledge that leads to the improvement of asset management outcomes.

Advanced computer simulation of the milling process

Process modelling is an integral part of any process industry. Several sugar factory models have been developed over the years to simulate the unit operations. An enhanced and comprehensive milling process simulation model has been developed to analyse the performance of the milling train and to assess the impact of changes and advanced control options for improved operational efficiency. The developed model is incorporated in a proprietary software package ‘SysCAD’. As an example, the milling process model has been used to predict a significant loss of extraction by returning the cush from the juice screen before #3 mill instead of before #2 mill as is more commonly done. Further work is being undertaken to more accurately model extraction processes in a milling train, to examine extraction issues dynamically and to integrate the model into a whole factory model.

Veracity of the archive : a research approach to the collection and verification of urban morphological records using qualitative data analysis software

Critical to the research of urban morphologists is the availability of historical records that document the urban transformation of the study area. However, thus far little work has been done towards an empirical approach to the validation of archival data in this field. Outlined in this paper, therefore, is a new methodology for validating the accuracy of archival records and mapping data, accrued through the process of urban morphological research, so as to establish a reliable platform from which analysis can proceed. The paper particularly addresses the problems of inaccuracies in existing curated historical information, as well as errors in archival research by student assistants, which together give rise to unacceptable levels of uncertainty in the documentation. The paper discusses the problems relating to the reliability of historical information, demonstrates the importance of data verification in urban morphological research, and proposes a rigorous method for objective testing of collected archival data through the use of qualitative data analysis software.

A recommendation system for predicting risks across multiple business process instances

This paper proposes a recommendation system that supports process participants in taking risk-informed decisions, with the goal of reducing risks that may arise during process execution. Risk reduction involves decreasing the likelihood and severity of a process fault from occurring. Given a business process exposed to risks, e.g. a financial process exposed to a risk of reputation loss, we enact this process and whenever a process participant needs to provide input to the process, e.g. by selecting the next task to execute or by filling out a form, we suggest to the participant the action to perform which minimizes the predicted process risk. Risks are predicted by traversing decision trees generated from the logs of past process executions, which consider process data, involved resources, task durations and other information elements like task frequencies. When applied in the context of multiple process instances running concurrently, a second technique is employed that uses integer linear programming to compute the optimal assignment of resources to tasks to be performed, in order to deal with the interplay between risks relative to different instances. The recommendation system has been implemented as a set of components on top of the YAWL BPM system and its effectiveness has been evaluated using a real-life scenario, in collaboration with risk analysts of a large insurance company. The results, based on a simulation of the real-life scenario and its comparison with the event data provided by the company, show that the process instances executed concurrently complete with significantly fewer faults and with lower fault severities, when the recommendations provided by our recommendation system are taken into account.

FaceXpress : an integrated software suite for facial emotion stimulus manipulation and facial measurement

The characterisation of facial expression through landmark-based analysis methods such as FACEM (Pilowsky & Katsikitis, 1994) has a variety of uses in psychiatric and psychological research. In these systems, important structural relationships are extracted from images of facial expressions by the analysis of a pre-defined set of feature points. These relationship measures may then be used, for instance, to assess the degree of variability and similarity between different facial expressions of emotion. FaceXpress is a multimedia software suite that provides a generalised workbench for landmark-based facial emotion analysis and stimulus manipulation. It is a flexible tool that is designed to be specialised at runtime by the user. While FaceXpress has been used to implement the FACEM process, it can also be configured to support any other similar, arbitrary system for quantifying human facial emotion. FaceXpress also implements an integrated set of image processing tools and specialised tools for facial expression stimulus production including facial morphing routines and the generation of expression-representative line drawings from photographs.

Virtual business role-play : leveraging familiar environments to prime stakeholder memory during process elicitation

Business process models have traditionally been an effective way of examining business practices to identify areas for improvement. While common information gathering approaches are generally efficacious, they can be quite time consuming and have the risk of developing inaccuracies when information is forgotten or incorrectly interpreted by analysts. In this study, the potential of a role-playing approach for process elicitation and specification has been examined. This method allows stakeholders to enter a virtual world and role-play actions as they would in reality. As actions are completed, a model is automatically developed, removing the need for stakeholders to learn and understand a modelling grammar. Empirical data obtained in this study suggests that this approach may not only improve both the number of individual process task steps remembered and the correctness of task ordering, but also provide a reduction in the time required for stakeholders to model a process view.

On Merging Business Process Management and Geographic Information Systems : Modeling and Execution of Ecological Concerns in Processes

Business Process Management describes a holistic management approach for the systematic design, modeling, execution, validation, monitoring and improvement of organizational business processes. Traditionally, most attention within this community has been given to control-flow aspects, i.e., the ordering and sequencing of business activities, oftentimes in isolation with regards to the context in which these activities occur. In this paper, we propose an approach that allows executable process models to be integrated with Geographic Information Systems. This approach enables process models to take geospatial and other geographic aspects into account in an explicit manner both during the modeling phase and the execution phase. We contribute a structured modeling methodology, based on the well-known Business Process Model and Notation standard, which is formalized by means of a mapping to executable Colored Petri nets. We illustrate the feasibility of our approach by means of a sustainability-focused case example of a process with important ecological concerns.

Noise Filtering of Process Execution Logs based on Outliers Detection

This paper presents a technique for the automated removal of noise from process execution logs. Noise is the result of data quality issues such as logging errors and manifests itself in the form of infrequent process behavior. The proposed technique generates an abstract representation of an event log as an automaton capturing the direct follows relations between event labels. This automaton is then pruned from arcs with low relative frequency and used to remove from the log those events not fitting the automaton, which are identified as outliers. The technique has been extensively evaluated on top of various auto- mated process discovery algorithms using both artificial logs with different levels of noise, as well as a variety of real-life logs. The results show that the technique significantly improves the quality of the discovered process model along fitness, appropriateness and simplicity, without negative effects on generalization. Further, the technique scales well to large and complex logs.

Process quality indicators targeting cognitive impairment to support quality of care for older people with cognitive impairment in emergency departments

Objectives The objective of this study was to develop process quality indicators (PQIs) to support the improvement of care services for older people with cognitive impairment in emergency departments (ED). Methods A structured research approach was taken for the development of PQIs for the care of older people with cognitive impairment in EDs, including combining available evidence with expert opinion (phase 1), a field study (phase 2), and formal voting (phase 3). A systematic review of the literature identified ED processes targeting the specific care needs of older people with cognitive impairment. Existing relevant PQIs were also included. By integrating the scientific evidence and clinical expertise, new PQIs were drafted and, along with the existing PQIs, extensively discussed by an advisory panel. These indicators were field tested in eight hospitals using a cohort of older persons aged 70 years and older. After analysis of the field study data (indicator prevalence, variability across sites), in a second meeting, the advisory panel further defined the PQIs. The advisory panel formally voted for selection of those PQIs that were most appropriate for care evaluation. Results In addition to seven previously published PQIs relevant to the care of older persons, 15 new indicators were created. These 22 PQIs were then field tested. PQIs designed specifically for the older ED population with cognitive impairment were only scored for patients with identified cognitive impairment. Following formal voting, a total of 11 PQIs were included in the set. These PQIs targeted cognitive screening, delirium screening, delirium risk assessment, evaluation of acute change in mental status, delirium etiology, proxy notification, collateral history, involvement of a nominated support person, pain assessment, postdischarge follow-up, and ED length of stay. Conclusions This article presents a set of PQIs for the evaluation of the care for older people with cognitive impairment in EDs. The variation in indicator triggering across different ED sites suggests that there are opportunities for quality improvement in care for this vulnerable group. Applied PQIs will identify an emergency services' implementation of care strategies for cognitively impaired older ED patients. Awareness of the PQI triggers at an ED level enables implementation of targeted interventions to improve any suboptimal processes of care. Further validation and utility of the indicators in a wider population is now indicated.

Technology adoption as a multi-stage process

This study proposes that technology adoption be considered as a multi-stage process constituting several distinct stages. Using the Theory of Planned Behaviour (TPB), Ettlie’s adoption stages and by employing data gathered from 162 owners of Small and Medium-sized Enterprises (SMEs), our findings show that the determinants of the intention to adopt packaged software fluctuate significantly across adoption stages.

Mining process risks and resource profiles

This research contributes novel techniques for identifying and evaluating business process risks and analysing human resource behaviour. The developed techniques use predefined indicators to identify process risks in individual process instances, evaluate overall process risk, predict process outcomes and analyse human resource behaviour based on the analysis of information about process executions recorded in event logs by information systems. The results of this research can help managers to more accurately evaluate the risk exposure of their business processes, to more objectively evaluate the performance of their employees, and to identify opportunities for improvement of resource and process performance.