Beyond Rigor and Relevance Towards Responsibility and Reverberation: Information Systems Research That Really Matters

This paper is an outcome of a panel discussion that was held during the 2005 International Conference on Information Systems (ICIS). The panel, titled, IS Research that Really Matters: Beyond the IS Rigor - Relevance Debate, was organized to foster a discussion on conducting IS research that is significant, in terms of impact, and responsible to the needs of stakeholders. To this end, panel members were asked to push the debate on IS research beyond the traditional arguments of rigor and relevance in research towards IS research that reverberates and is responsible. In doing so, the panel members shared their views on the definition of significant research, who are the stakeholders of IS research and what are their needs, and how do we move the field ahead

Designing a Process Mining-Enabled Decision Support System for Business Process Standardization in ERP Implementation Projects

Process standardization allows to optimize ERP systems and is a nec-essary step prior to ERP implementation projects. Traditional approaches to standardizing business processes are based on manually created "de-jure" process models, which are distorted, error-prone, simplistic, and often deviating from process reality. Theoretically embedded in the organizational contingency theory as kernel theory, this paper employs a design science approach to design a process mining-enabled decision support system (DSS) which combines bottom-up process mining models with manually added top-down standardization infor-mation to recommend a suitable standard process specification from a repository. Extended process models of the as-is process are matched against a repository of best-practice standard process model using an attributebased process similarity matching algorithm. Thus, the DSS aims to reduce the overall costs of process standardization, to optimize the degree of fit between the organization and the implemented processes, and to minimize the degree of organizational change re-quired in standardization and ERP implementation projects. This paper imple-ments a working prototype instantiation in the open-source process analytics platform Apromore based on a real-life event log and standardization attributes for the Purchase-to-Pay and Order-to-Cash processes from three SAP R/3 ERP systems at the industry partner

Leadership Competencies for Digital Transformation : Evidence from Multiple Cases

Digital transformation (DT) is disrupting industrial organizations, which require significant changes in their properties to remain competitive. This calls for strong leadership to drive this transformation. However, what leadership competencies are required to lead DT impactfully is unclear. Therefore, we seek to identify the key leadership competencies by employing a qualitative, grounded theory approach. By conducting interviews of ten DT experts from two hardcore industrial organizations, we highlight five key leadership competencies that industrial organizations need to develop in their leaders: digital vision, digital knowledge, failing fast, empowerment, and managing diverse teams. The results of this study will help industrial organizations to strategically prepare their leadership for the requirements of DT.©2020 Springer. This is a post-peer-review, pre-copyedit version of an article published in Advances in Human Factors, Business Management and Leadership: Proceedings of the AHFE 2020 Virtual Conferences on Human Factors, Business Management and Society, and Human Factors in Management and Leadership, July 16-20, 2020, USA. The final authenticated version is available online at: http://dx.doi.org/0.1007/978-3-030-50791-6_11.fi=vertaisarvioitu|en=peerReviewed

Binary choice models for external auditors decisions in Asian banks

Summarization: The present study investigates the efficiency of four classification techniques, namely discriminant analysis, logit analysis, UTADIS multicriteria decision aid, and nearest neighbours, in the development of classification models that could assist auditors during the examination of Asian commercial banks. To develop the auditing models and examine their classification ability, the dataset is split into two distinct samples. The training sample consists of 1,701 unqualified financial statements and 146 ones that received a qualified opinion over the period 1996–2001. The models are tested in a holdout sample of 527 unqualified financial statements and 52 ones that received a qualified opinion over the period 2002–2004. The results show that the developed auditing models can discriminate between financial statements that should receive qualified opinions from the ones that should receive unqualified opinions with an out-of-sample accuracy around 60%. The highest classification accuracy is achieved by UTADIS, followed by logit analysis, nearest neighbours and discriminant analysis. Both financial variables and the environment in which banks operate appear to be important factors.Presented on: Operational Research, An International Journa

Individual-environment interactions in swimming: The smallest unit for analysing the emergence of coordination dynamics in performance?

Displacement in competitive swimming is highly dependent on fluid characteristics, since athletes use these properties to propel themselves. It is essential for sport scientists and practitioners to clearly identify the interactions that emerge between each individual swimmer and properties of an aquatic environment. Traditionally, the two protagonists in these interactions have been studied separately. Determining the impact of each swimmer’s movements on fluid flow, and vice versa, is a major challenge. Classic biomechanical research approaches have focused on swimmers’ actions, decomposing stroke characteristics for analysis, without exploring perturbations to fluid flows. Conversely, fluid mechanics research has sought to record fluid behaviours, isolated from the constraints of competitive swimming environments (e.g. analyses in two-dimensions, fluid flows passively studied on mannequins or robot effectors). With improvements in technology, however, recent investigations have focused on the emergent circular couplings between swimmers’ movements and fluid dynamics. Here, we provide insights into concepts and tools that can explain these on-going dynamical interactions in competitive swimming within the theoretical framework of ecological dynamics

A Survey of Bayesian Statistical Approaches for Big Data

The modern era is characterised as an era of information or Big Data. This has motivated a huge literature on new methods for extracting information and insights from these data. A natural question is how these approaches differ from those that were available prior to the advent of Big Data. We present a review of published studies that present Bayesian statistical approaches specifically for Big Data and discuss the reported and perceived benefits of these approaches. We conclude by addressing the question of whether focusing only on improving computational algorithms and infrastructure will be enough to face the challenges of Big Data