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Public blockchain
(2020)
Blockchain has the potential to change business transactions to a major extent. Thereby, underlying consensus algorithms are the core mechanism to achieve consistency in distributed infrastructures. Their application aims for transparency and accountability in societal transactions. As a result of missing reviews holistically covering consensus algorithms, we aim to (1) identify prevalent consensus algorithms for public blockchains, and (2) address the resource perspective with a sustainability consideration (whereby we address the three spheres of sustainability). Our systematic literature review identified 33 different consensus algorithms for public blockchains. Our contribution is twofold: first, we provide a systematic summary of consensus algorithms for public blockchains derived from the scientific literature as well as real-world applications and systemize them according to their research focus; second, we assess the sustainability of consensus algorithms using a representative sample and thereby highlight the gaps in literature to address the holistic sustainability of consensus algorithms.
As Industry 4.0 infrastructures are seen as highly evolutionary environment with volatile, and time-dependent workloads for analytical tasks, particularly the optimal dimensioning of IT hardware is a challenge for decision makers because the digital processing of these tasks can be decoupled from their physical place of origin. Flexible architecture models to allocate tasks efficiently with regard to multi-facet aspects and a predefined set of local systems and external cloud services have been proven in small example scenarios. This paper provides a benchmark of existing task realization strategies, composed of (1) task distribution and (2) task prioritization in a real-world scenario simulation. It identifies heuristics as superior strategies.
The idea of the continuous improvement process (CIP) helps companies to continuously improve their operation and thereby contributes to their competitiveness. Through digi tization, new potentials emerge to solve known CIP issues. This contribution specifically addresses the individual motivation of employees to contribute to the CIP. Typically, related initiatives lack contributions over time. The use of gamification is a promising way to achieve continuous participation by addressing the individual needs of participants. While the use of extrinsic motivation elements is common in practice, the idea of this approach is to specifically address intrinsic motivations which serve as a long-term motivator. This article contributes to a gam-ification concept for the continuous improvement process. The main results include an adapted CIP, a gamification concept, and a market mechanism. Furthermore, the concept is implemented and demonstrated as a prototype in an online platform.
Software platforms allow for the extension of features by third-party contributors. Thereby, platform innovation is an important aspects of platforms attractiveness for users and complementors. While previous research focused the introduction of new features, the aspect of feature removal and discontinued features on software platforms has been disregarded. To explore the phenomenon and motivations for feature removal on software platforms, a review of recent literature is provided. To illustrate the existence of and motivations for feature removal, a case study of the browser platform Mozilla Firefox is presented. The results reveal feature removal to regularly occur on browser platforms for user- and developer-related features. Frequent reasons for feature removal involve unused features, security concerns, and bugs. Related motivations for feature removal are discussed from the platform owner's perspective. Implications for complementors and users are highlighted.
The digitalization of value networks holds out the prospect of many advantages for the participating compa- nies. Utilizing information platforms, cross-company data exchange enables increased efficiency of collab- oration and offers space for new business models and services. In addition to the technological challenges, the fear of know-how leakage appears to be a significant roadblock that hinders the beneficial realization of new business models in digital ecosystems. This paper provides the necessary building blocks of digital participation and, in particular, classifies the issue of trust creation within it as a significant success factor. Based on these findings, it presents a solution concept that, by linking the identified building blocks, offers the individual actors of the digital value network the opportunity to retain sovereignty over their data and know-how and to use the potential of extensive networking. In particular, the presented concept takes into account the relevant dilemma, that every actor (e. g. the machine users) has to be able to control his commu- nicated data at any time and have sufficient possibilities for intervention that, on the one hand, satisfy the need for protection of his knowledge and, on the other hand, do not excessively diminish the benefits of the system or the business. Taking up this perspective, this paper introduces dedicated data sovereignty and shows a possible implementation concept.
Future ERP Systems
(2021)
This paper presents a research agenda on the current generation of ERP systems which was developed based on a literature review on current problems of ERP systems. The problems are presented following the ERP life cycle. In the next step, the identified problems are mapped on a reference architecture model of ERP systems that is an extension of the three-tier architecture model that is widely used in practice. The research agenda is structured according to the reference architecture model and addresses the problems identified regarding data, infrastructure, adaptation, processes, and user interface layer.
Expanding modeling notations
(2021)
Creativity is a common aspect of business processes and thus needs a proper representation through process modeling notations. However, creative processes constitute highly flexible process elements, as new and unforeseeable outcome is developed. This presents a challenge for modeling languages. Current methods representing creative-intensive work are rather less able to capture creative specifics which are relevant to successfully run and manage these processes. We outline the concept of creative-intensive processes and present an example from a game design process in order to derive critical process aspects relevant for its modeling. Six aspects are detected, with first and foremost: process flexibility, as well as temporal uncertainty, experience, types of creative problems, phases of the creative process and individual criteria. By first analyzing what aspects of creative work modeling notations already cover, we further discuss which modeling extensions need to be developed to better represent creativity within business processes. We argue that a proper representation of creative work would not just improve the management of those processes, but can further enable process actors to more efficiently run these creative processes and adjust them to better fit to the creative needs.
Yes, we can (?)
(2021)
The COVID-19 crisis has caused an extreme situation for higher education institutions around the world, where exclusively virtual teaching and learning has become obligatory rather than an additional supporting feature. This has created opportunities to explore the potential and limitations of virtual learning formats. This paper presents four theses on virtual classroom teaching and learning that are discussed critically. We use existing theoretical insights extended by empirical evidence from a survey of more than 850 students on acceptance, expectations, and attitudes regarding the positive and negative aspects of virtual teaching. The survey responses were gathered from students at different universities during the first completely digital semester (Spring-Summer 2020) in Germany. We discuss similarities and differences between the subjects being studied and highlight the advantages and disadvantages of virtual teaching and learning. Against the background of existing theory and the gathered data, we emphasize the importance of social interaction, the combination of different learning formats, and thus context-sensitive hybrid learning as the learning form of the future.
Increasingly fast development cycles and individualized products pose major challenges for today's smart production systems in times of industry 4.0. The systems must be flexible and continuously adapt to changing conditions while still guaranteeing high throughputs and robustness against external disruptions. Deep rein- forcement learning (RL) algorithms, which already reached impressive success with Google DeepMind's AlphaGo, are increasingly transferred to production systems to meet related requirements. Unlike supervised and unsupervised machine learning techniques, deep RL algorithms learn based on recently collected sensor- and process-data in direct interaction with the environment and are able to perform decisions in real-time. As such, deep RL algorithms seem promising given their potential to provide decision support in complex environments, as production systems, and simultaneously adapt to changing circumstances. While different use-cases for deep RL emerged, a structured overview and integration of findings on their application are missing. To address this gap, this contribution provides a systematic literature review of existing deep RL applications in the field of production planning and control as well as production logistics. From a performance perspective, it became evident that deep RL can beat heuristics significantly in their overall performance and provides superior solutions to various industrial use-cases. Nevertheless, safety and reliability concerns must be overcome before the widespread use of deep RL is possible which presumes more intensive testing of deep RL in real world applications besides the already ongoing intensive simulations.
Enterprise systems have long played an important role in businesses of various sizes. With the increasing complexity of today’s business relationships, specialized application systems are being used more and more. Moreover, emerging technologies such as artificial intelligence are becoming accessible for enterprise systems. This raises the question of the future role of enterprise systems. This minitrack covers novel ideas that contribute to and shape the future role of enterprise systems with five contributions.
Enterprise Resource Planning (ERP) systems are critical to the success of enterprises, facilitating business operations through standardized digital processes. However, existing ERP systems are unsuitable for startups and small and medium-sized enterprises that grow quickly and require adaptable solutions with low barriers to entry. Drawing upon 15 explorative interviews with industry experts, we examine the challenges of current ERP systems using the task technology fit theory across companies of varying sizes. We describe high entry barriers, high costs of implementing implicit processes, and insufficient interoperability of already employed tools. We present a vision of a future business process platform based on three enablers: Business processes as first-class entities, semantic data and processes, and cloud-native elasticity and high availability. We discuss how these enablers address current ERP systems' challenges and how they may be used for research on the next generation of business software for tomorrow's enterprises.
While Information Systems (IS) Research on the individual and workgroup level of analysis is omnipresent, research on the enterprise-level IS is less frequent. Even though research on Enterprise Systems and their management is established in academic associations and conference programs, enterprise-level phenomena are underrepresented. This minitrack provides a forum to integrate existing research streams that traditionally needed to be attached to other topics (such as IS management or IS governance). The minitrack received broad attention. The three selected papers address different facets of the future role of enterprise-wide IS including aspects such as carbonization, ecosystem integration, and technology-organization fit.
Enterprise solutions, specifically enterprise systems, have allowed companies to integrate enterprises’ operations throughout. The integration scope of enterprise solutions has increasingly widened, now often covering customer activities, activities along supply chains, and platform ecosystems. IS research has contributed a wide range of explanatory and design knowledge dealing with this class of IS. During the last two decades, many technological as well as managerial/organizational innovations extended the affordances of enterprise solutions—but this broader scope also challenges traditional approaches to their analysis and design. This position paper presents an enterprise-level (i.e., cross-solution) perspective on IS, discusses the challenges of complexity and coordination for IS design and management, presents selected enterprise-level insights for IS coordination and governance, and explores avenues towards a more comprehensive body of knowledge on this important level of analysis.
While Information Systems Research exists at the individual and workgroup levels, research on IS at the enterprise level is less common. The potential synergies between the study of enterprise systems (ES) and related fields have been underexplored and often treated as separate entities. The ongoing challenge is to seamlessly integrate technological advances and align business processes across organizations. While systems integration within an organization is common, changes occur when industry and ecosystem perspectives come into play. The four selected papers address different facets of the future role of enterprise ecosystems, including implementation challenges, ecosystem boundaries, and B2B platform specifics.
Enterprise Resource Planning (ERP) system customization is often necessary because companies have unique processes that provide their competitive advantage. Despite new technological advances such as cloud computing or model-driven development, technical ERP customization options are either outdated or ambiguously formulated in the scientific literature. Using a systematic literature review (SLR) that analyzes 137 definitions from 26 papers, the result is an analysis and aggregation of technical customization types by providing clearance and aligning with future organizational needs. The results show a shift from ERP code modification in on-premises systems to interface and integration customization in cloud ERP systems, as well as emerging technological opportunities as a way for customers and key users to perform system customization. The study contributes by providing a clear understanding of given customization types and assisting ERP users and vendors in making customization decisions.