Guiding Design Principle Projects: A Canvas for Young Design Science Researchers

Particularly young researchers face challenges in organizing large design science research (DSR) projects and often struggle to capture, communicate, and reflect on important components to produce purposeful outcomes. Making informed decisions at the project start, such as selecting suitable kernel theories and development procedures, is of great relevance because they affect the entire design process and the resulting design products. Although DSR can produce different types of outcomes, from more situational artifacts to more abstract design knowledge, scholars point to the need for generalizing insights collected in such projects to advance the knowledge base. As design principles are among the prevailing forms of such design knowledge, this paper builds a visual inquiry tool—represented as a canvas—that navigates researchers through common components for crafting design principles and leverages collaborative reflections on essential project decisions. To build our canvas, we adapt inquiry-based learning (IBL) guidelines and visual inquiry tools to DSR education. Evaluations with doctoral students revealed promising indications for the canvas’s applicability and usefulness in guiding iterative DSR projects, reflecting on basic components, and communicating work-in-progress to other scholars and practice. Overall, we complement the body of DSR literature by providing an educational visual inquiry tool for producing design principles

Organizational, Sociological and Procedural Uncertainties in Statistical and Machine Learning: A Systematic Literature Review

Driven by the potential of digitalization, statistical learning and machine learning methods are commonly used for scheduling complex processes or forecasting in supply chain domains. However, trust in such methods is hampered by uncertainties in data quality, data exchange platforms, and data processing, affecting its traceability and reliability. Decision-relevant output provided by such methods is prone to trust issues in the data used for training, in the resulting model, and in the infrastructure in which the model is embedded. Considering the vulnerability of supply chains, wrong decisions have far-reaching consequences, raising the question of to what extent systems alone should be trusted for strategic, operational, and tactical decision-making. In this paper, we take a multidisciplinary perspective with the intention to analyze trust in statistical learning and machine learning methods from an organizational, sociological, and procedural perspective. The information base for this article is gathered through a systematic literature review. The central results of our research are a concept matrix comparing papers based on relevant criteria derived from literature and subsequent findings derived from this matrix. We encourage researchers in the fields of supply chain management, sociology, and statistics or machine learning to open up for interdisciplinary research and to build upon our findings

Evaluation of (De-)Centralized IT technologies in the fields of Cyber-Physical Production Systems

In the course of the digital transformation, organizations are not only facing increasing volatility of the markets, but also increasing customer requirements and thus an increasing complexity in production and logistics systems. Therefore, production plants need to become more flexible by transforming conventional production systems to Cyber-physical Production Systems (CPPS). CPPS allow organizations to dynamically react to fluctuations in demand and markets and to introduce new product lines quickly and effectively. The challenge in implementing CPPS is to handle and store relevant data streams between Cyber-physical objects in a secure but transparent way. As CPPS involve a high level of decentralization, the data storage can either be combined with centralized IT-solutions like a Cloud or utilize decentralized IT-technologies like Edge Computing or Distributed Ledger Technologies (DLT) like Blockchains. The paper addresses the suitability of centralized and decentralized technologies in terms of dealing with data streams in the fields of CPPS. For this purpose, based on a paper exploration, appropriate evaluation criteria are derived, followed by a comparison of exemplary centralized and decentralized technologies. The outcome is a qualitative evaluation of the supplement of each technology regarding its suitability of dealing with data streams

Designing a Blockchain-Based Digital Twin for Cyber-Physical Production Systems

Trust in all processes on the shopfloor is crucial for the success of a production process, especially in cross company scenarios such as shared manufacturing, in which independent parties interact with each other. A cyber-physical production system (CPPS) contributes to the vision of a decentralized, self-configuring and flexible production. Digital twins (DTs) can visualize the material, information and financial flows in real time and improve the process transparency of such production systems. The efficiency of digital twins depends on the integrity of the provided data, especially if data is shared across company borders. Due to its characteristics such as immutability and transparency, blockchain technology (BCT) provides a basis for establishing the desired trust in the systems on the shopfloor. This paper proposes the design of a BCT-based DT in CPPS. The design is demonstrated by a prototype including smart contracts attached to a CPPS simulation model visualizing the information and material flow. Tasks are decentrally allocated, deployed and safely documented via blockchain. The demonstrator is revealing supplementary benefits in terms of transparency provided by the BCT. This paper further examines whether BCT can enrich existing solutions and provide a reliable information basis for profound data and process analysis

Categorizing Challenges And Potentials Of Digital Industrial Platforms

In complex supply chains, digital platforms play an emerging role as an infrastructure for network-based collaboration of industrial companies to stay competitive. Participating in a platform business offers a range of new potentials, while also introducing new challenges. Awareness of these is crucial for both users and providers to make informed decisions. Thus, this paper provides an overview about typical challenges and potentials from the perspective of potential or actual digital industrial platform users to support decision making processes. Against that backdrop, a descriptive study is conducted in the field of industrial service platforms motivated from two sides. Expert workshops are held to examine the practical opportunities and hurdles. The findings are then compared to those identified in literature. Then, the results are organized into a category system that highlights the key challenges and potentials for users as well as providers of digital industrial platforms

Loneliness and social media: A qualitative investigation of young people's motivations for use and perceptions of social networking sites

The democratisation of Internet access has incrementally changed every domain of activity and has created new business and economic models. From answering work emails to learning a new language, shopping, booking medical appointments or managing one’s finances, almost everything is attainable at the click of a button. The added implications of the rapid rise of social networking websites (SNSs), such as Facebook, Twitter, Instagram or Snapchat, have further contributed to changing the way we communicate and build new friendships. Indeed most of our social relationships are now being ‘increasingly developed and maintained online’ (Nowland, Necka & Cacioppo, 2017: 1). Ostensibly, despite improved Internet access and enhanced social connectedness, modern societies are struggling to combat loneliness. It is reported to affect people of all ages, especially young adults (16-24 and 25-34 years old) who are avid Internet and social media users (see Office for National Statistics, 2018)

Design Knowledge for GAIA-X-compliant Ecosystems: A Literature Review

Integrating digital technologies offer companies a range of potentials for optimizing business processes, exploring new business models and collaborating along value chains to co-create value. However, this integration increases complexity, especially within SMEs that lack extensive resources to drive data transformation. GAIA-X offers potential solutions in form of federated services as a low-threshold way to participate in federated data ecosystems. Thus, in this paper we survey the current state of research on GAIA-X by means of a literature review extracting and collecting design knowledge as well as to prepare further implementation within the scope of our research project. Therefore, we build a concept matrix in which we differentiate the identified body of knowledge by three concepts with 18 characteristic expressions in total. Our analysis of the identified papers highlights architectural approaches for designing a GAIA-X compatible data ecosystem, augmented by additional factors to consider when designing these ecosystems

Potentials Of Blockchain In Crowdsourcing Platforms – An Outlook For Industrial Services

Companies increasingly outsource services with the intention to disseminate risks and workload (problem) with other organizations. Reasons for that may be the lack of internal expertise, reduced execution costs, and network effects such as focus on the core business. Crowdsourcing is a way of disseminate the workload, utilizing external expertise and solving problems of a project with other, partly unknown, network participants. The goal of crowdsourcing is to separate responsibility and to balance the workload of employees (peer) or to make use of suitable external workforces coordinated by network mechanisms (platform). Crowdsourcing appears in an ambivalent way and needs regulating and participatory structures of employment. Due to the fact that a failure of a single entity may lead to the failure of the whole project, the mutually unknown participants have to rely on each other’s quality (performance). Cooperations are prone to information asymmetry and its corresponding uncertainty in terms of the partners’ behaviour which leads to the question of trust between the cooperating partners (principal and peer). This paper addresses the entities of a crowdsourcing system under the scope of the principal agent theory and its underlying behavioural assumptions. Five essential elements will be derived: principal, peer, problem, platform and performance (5 Ps). Based on this, the potentials of the blockchain technology will be explored by reflecting its functionalities to the derived elements and its contributions to ensure trust despite of information asymmetry in crowdsourcing platforms

Heavy-light mesons from the AdS/CFT correspondence

We propose a holographic description of heavy-light mesons, i.e. of mesons containing a light and a heavy quark. In the semi-classical string limit, we look at the dynamics of strings tied between two D7 branes. We consider this setup both in an AdS background and in the non-supersymmetric Constable-Myers geometry which induces chiral symmetry breaking. We compute the meson masses in each case. Finally we discuss the results relevance for phenomenological comparison to the physical b-quark sector