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

Chuanwen Dong, Akanksha Saxena, Markus Bick, Andrea Sabia — 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.

Requirements Elicitation Using a Combination of Prototypes and Business process modeling

Tarik Kraljić

One of the biggest challenge in ERP implementation process is system requirements gathering and the communication gap between different stakeholders. The ERP system analysts/integrators tend to speak with technical terms while the customer and end-users prefer to use the language used in their daily business and to see real ERP application in action. As a result, the ERP integrators may not have a clear idea what kind of system they should deliver, and the customer and end-users are often surprised with the final product which does not fulfil their expectations and solve the problems.

Agile Software Engineering Practices in SAP ERP project

The Enterprise Resource Planning (ERP) implementation is a complex and active process, one that involves a mixture of technological and organizational interactions. Often it is the largest IT project that an organization has ever launched and requires a mutual fit of system and organization. The concept of an ERP implementation supporting business processes across different departments in the organization is not a generic, rigid, and uniform process - it is a vivid one and depends on a number of different factors. As a result, the issues addressing the ERP implementation process have been one of the major concerns in the industry. Therefore, the ERP implementation process receives profound attention from practitioners and scholars in its academic or industry papers. However, research on ERP systems so far has been mainly focused on diffusion, use, and impact issues. Less attention has been given to the methods/methodologies used during the configuration and the implementation of ERP systems; even though they are commonly used in practice, they still remain largely unexplored and undocumented in the Information Systems research domain. Furthermore, research on Agile Software Engineering Practices in ERP Implementations context is almost nonexistent. Many IT specialists find agile management frameworks positive, but ask themselves whether these can also cope with the complex adjustments of ERP systems. The answer is quite simple: agile management frameworks, in particular Scrum, were developed for the exact purpose of enabling the successful execution of large and complex projects. Depending on the size of the company, an ERP project including preparation can take over a year – or it can become a long-runner that eats up resources. One reason for this: if projects are handled in line with traditional procedural models, lengthy integration and acceptance tests are not carried out until the end. So, at the end of the development the detected errors and change requests pile up and delivery is delayed. This study is a response to the frequent calls for industrial case studies on agile software development (Dingsøyr et al. 2012; Dybå and Dingsøyr 2008). This paper is useful to researchers who are interested in ERP implementation methodologies and frameworks. The Paper also aims at the professional ERP community involved in the process of ERP implementation by promoting a better understanding of ERP implementation methodologies and frameworks, their variety, and future development.

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.