AIS Transactions on Enterprise Systems

The Relationship of Computer Aptitude, Positive Affect, and Openness Personality Traits on Learning Enterprise Systems

Mary Sumner

Enterprise Resource Planning (ERP) systems are complex enterprise information systems. They are the backbone for running most enterprises and support integrated business processes across the supply chain, including sales and distribution, materials management, financial accounting, and managerial accounting processes. The need for individuals who can learn to use these systems successfully is a recurring challenge and is a talent acquisition priority for organizations. This research seeks to explore the relationships between computer aptitude, Positive Affect, and the Openness personality trait in the successful learning of ERP systems. Structural equation modeling was used to test the research hypotheses. The results revealed that users’ cognitive aptitude for computing and Positive Affect were positively related to their ERP system learning performance. Furthermore, users’ Openness personality trait was positively related to their Positive Affect.

Success Factors in Efficient Mergers & Acquisitions Activities:

Markus Böhm, Sebastian Floerecke, Alexander Herzfeldt, Dominik Knoblich — Sun, 25 Jun 2023 00:00:00 +0000

In 2021, the global mergers & acquisitions (M&A) market remained strong, with transaction volumes reaching $5.9 trillion and an increasing number of large deals. Despite the strategic impact and the high priority of every transaction, many of them fail to deliver the anticipated value due to inferior implementation, both from a post-merger IT integration (IT PMI) and an IT carve-out perspective. This paper explains how one of the world’s largest engineering companies (TURBO) has developed IT M&A capabilities to ensure both efficient post-merger IT-PMI and IT-carve-out projects. Their key to success relies on two principles, (1) standardization of the IT integration and respectively IT separation (carve-out) process, and (2) standardization of the enterprise architecture. By establishing these principles, TURBO managed to reduce both time and costs of its IT integration and IT carve-out projects by on average 40 %. Based on this case study, the paper synthesizes four success factors that can inform managers of M&A active organizations to successfully build IT-PMI and IT-carve-out capabilities.

On the Journey to AI Maturity

Thu, 19 Jan 2023 00:00:00 +0000

Artificial Intelligence (AI) has recently become pivotal in day-to-day business. However, surveys show that underlying, systemic issues – aside from AI-related aspects – hinder its enterprise-wide adoption. In this study, we aim to understand the role of this new breed of providers on the path to AI maturity and enterprise-wide adoption. We collect secondary data (i.e., surveys) from 154 white papers published by companies implementing AI solutions and apply descriptive and thematic analysis to understand the current challenges and opportunities of AI implementation. The thematic analysis involves topic modelling using natural language-processing algorithms. Our results demonstrate that, despite AI service providers addressing – at least in part – the major challenges faced by clients, there is still a gap between the skills demanded by end-users, and skills possessed by and focused on AI service providers.

Studying Digital Initiatives: Applying Established Perspectives to Emerging Digital Phenomena

Kazem Haki, Stephan Aier, Robert Winter

The information systems (IS) discipline is witnessing a shift in topical areas due to an ever-growing pervasiveness of digital technologies. Digitalization is rapidly transforming the fabric and organizing logics of firms and has introduced new business practices and opportunities. To catch up with the digitalization wave, IS scholars have been exposing the IS literature to a plethora of brand-new phenomena and theories. While such a considerable topical shift toward fashionable topics is necessary to maintain the dynamics of the IS discipline, it may compromise the cumulative nature of knowledge development. In this paper, we afford a reflexive discussion on the use of existing established theories and research approaches in studying emerging digital phenomena. To this end, we demonstrate the use of stakeholder theory and a two-dimensional research approach, as exemplars of existing established research perspectives, to the topic of digital platforms, as one of the digital phenomena that has recently drawn the attention of IS scholars.

Design of a Neuronal Training Modeling Language

Marcus Grum, Werner Hiessl, Karl Maresch, Norbert Gronau — Thu, 25 Mar 2021 00:00:00 +0000

As the complexity of learning task requirements, computer infrastructures and knowledge acquisition for artificial neuronal networks (ANN) is increasing, the communication about ANN is challenging. An efficient, transparent and failure-free design of learning tasks by models is not supported by any tool at all. For this purpose, particular the consideration of data, information, and knowledge on the base of an integration with knowledge-intensive business process models and a process-oriented knowledge management are attractive. With the aim of making the design of learning tasks expressible by models, this paper proposes a graphical modeling language called Neuronal Training Modeling Language (NTML), which allows the repetitive use of learning designs. An example ANN project of AI-based dynamic GUI adaption exemplifies its use as a first demonstration.

Embedding Robotic Process Automation into Process Management

Vikram Sethi, Anand Jeyaraj, Kevin Duffy, Berkwood Farmer — Tue, 28 Jul 2020 00:00:00 +0000

XYZ Company routinely faced penalties imposed by the United States Internal Revenue Service (IRS) for non-compliance in depositing federal withholding taxes related to the managed benefits plans for its clients. Since the rules for depositing the federal taxes were complex and differed between the benefits plans, it was common for XYZ Company to accrue penalties imposed by the IRS. Desiring to eliminate penalties by complying 100% with the IRS guidelines, XYZ Company considered various solutions. Finally, XYZ Company implemented a Robotic Process Automation (RPA) solution using the open source tool—taskt—to achieve 100% compliance in depositing federal withholding taxes and eliminate penalties. Discussion of solution improvements, reflection and next steps, technical challenges, lessons learned, and design science retrospective is provided.

An approach to model forgetting

Jennifer Haase, Christof Thim — Wed, 03 Jun 2020 00:00:00 +0000

This paper aims to investigate the possibility to include aspects of forgetting into business process modeling. To date, there is no possibility to model forgotten or to-be- forgotten elements beyond the mere deletion. On a first attempt, we focus on the individual level and model knowledge transformation within a single person. Using the Knowledge Model Description Language, we propose ways to include different forms of forgetting into the realm of modeling tools. Using data from an experimental setting within an assembly line production environment, the usability of those new modeling tools is tested. So far, the applicability of modeling features for forgetting on the individual level is mostly restricted to a research context. However, clear requirements to transfer the tools onto the team- and organizational level are set out.

Multiagent-Based Simulation of Intentional Forgetting

Lukas Reuter, Jan Ole Berndt, Ingo J. Timm

In today's organizations, information as well as knowledge availability and quantity are driving complex decision-making tasks. Especially for intelligent agents, increasing knowledge-bases for complex computations lead to a lower efficiency of their inference mechanisms due to their computational limitations. In contrast to artificial intelligence, bounded cognitive capacity is a well-known problem in psychology. In order to cope with a limited capacity, humans adapt their knowledge and delete, override, suppress, or sort out outdated information, i.e., they forget.
Due to the similarity of psychological and artificial intelligence research, we adopt an interdisciplinary view of modeling and analyzing forgetting as an intentional process. In this paper, we adopt intentional forgetting from a distributed artificial intelligence perspective. Our main objective is to introduce a formal agent architecture for distributing and adapting (meta-)knowledge by intentional forgetting. We show exemplary for Discourse Agents, which are based on the well-known Belief-Desire-Intention paradigm, the formalization for capabilities and their adaptation.

Intentional Forgetting in Socio-Digital Work Systems

Wed, 08 May 2019 00:00:00 +0000

Future work environments offer numerous technical applications to manage increasing amounts of information for organizations, teams, and individuals. Psychological concepts of intentional forgetting (IF) can be applied to improve the performance of work systems or to extend cognitive capacities of humans in technical systems. Different IF mechanisms have been suggested for assisting technology-aided IF, such as: (1) filtering of irrelevant or distressful information (e.g., by suppressing, deleting, or selecting), (2) delegating tasks from human to digital agents, changing roles, and reorganizing socio-digital work systems, or (3) systematic (re-)placement of retrieval cues or triggers to generate or suppress behavior. Due to these different underlying IF mechanisms, the implementation of IF at individual, team, and organizational level will differ substantially between work areas or systems. In order to gain a better understanding of how socio-digital applications of IF impact human behavior and reactions, it is necessary to (a) differentiate between relevant characteristics of socio-digital IF systems and (b) gain an understanding of how these characteristics impact users’ attitudes and performance. Thus, the present paper aims to classify and compare these characteristics of different applications of IF and introduces variables and methods to study psychological effects on users’ behavior, experience, and affective reactions.

Evaluation of Self-Reflection Training to Uncover Tacit Knowledge in a Learning Organization

Victoria Hasenstab, Manuel Pietzonka — Wed, 08 May 2019 00:00:00 +0000

By working in different projects and different teams over years, employees acquire tacit knowledge unconsciously. It is represented through experiences and is intangible. This knowledge is embodied in our routines. Therefore, it is difficult to verbalize tacit knowledge. This paper introduces a practical approach for companies to use their tacit knowledge in order to become a learning organization. The results of a semi-standardized face-to-face-interview survey with participants (n=10) show to what extent a self-reflection can contribute to uncover and share tacit knowledge in an IT-organization. The answers of the participants were recorded, utilized, coded and analyzed qualitatively. The results show that the intervention can encourage the process of uncovering tacit knowledge. It is possible for the employees to see the past project problems from different perspectives via self-reflection. Thereby they are able to uncover the tacit dimension of their experience and gain new insights.