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Benchmarking transaction and analytical processing systems : the creation of a mixed workload benchmark and its application
Systems for Online Transaction Processing (OLTP) and Online Analytical Processing (OLAP) are currently separate. The potential of the latest technologies and changes in operational and analytical applications over the last decade have given rise to the unification of these systems, which can be of benefit for both workloads. Research and industry have reacted and prototypes of hybrid database systems are now appearing. Benchmarks are the standard method for evaluating, comparing and supporting the development of new database systems. Because of the separation of OLTP and OLAP systems, existing benchmarks are only focused on one or the other. With the rise of hybrid database systems, benchmarks to assess these systems will be needed as well. Based on the examination of existing benchmarks, a new benchmark for hybrid database systems is introduced in this book. It is furthermore used to determine the effect of adding OLAP to an OLTP workload and is applied to analyze the impact of typically used optimizations in the historically separate OLTP and OLAP domains in mixed-workload scenarios.
Book
Smart Factory Implementation and Process Innovation
The development of novel digital technologies connected to the Internet of Things, along with advancements in artificial intelligence and automation, is enabling a new wave of manufacturing innovation. “Smart factories” will leverage industrial equipment that communicates with users and with other machines, automated processes, and mechanisms to facilitate real-time communication between the factory and the market to support dynamic adaptation and maximize efficiency. Smart factories can yield a range of benefits, such as increased process efficiency, product quality, sustainability, and safety and decreased costs. However, companies face immense challenges in implementing smart factories, given the large-scale, systemic transformation the move requires. We use data gathered from in-depth studies of five factories in two leading automotive manufacturers to analyze these challenges and identify the key steps needed to implement the smart factory concept. Based on our analysis, we offer a preliminary maturity model for smart factory implementation built around three overarching principles: cultivating digital people, introducing agile processes, and configuring modular technologies.
Journal Article
Competing values leadership
\"This book serves as the key source for understanding the Competing Values Framework, one of the most widely used and highly cited frameworks in the world. The authors, who have been at the foundation of developing, applying and studying this framework for over three decades, explain how it helps foster successful leadership, improve organizational effectiveness and promote value creation.\"-- Publisher's description.
Book
Operations Management in ChinaCraig Seidelson
This book provides understanding how to make and buy products from China. The author takes readers inside Chinese organizations and shows how factories are built, labor is managed, goods are sourced, quality is controlled, and logistics are handled. Through this immersion experience, readers are able to see the opportunities and pitfalls in manufacturing in China.
Book
Modellierung und Analyse von Geschaftsprozessen: Grundlagen und Ubungsaufgaben mit Losungen
Buch bietet einen leicht verständlichen Einstieg in die Modellierung und Analyse von Geschäftsprozessen. Aufbauend auf Grundlagen zur Modellbildung und Modellerstellung werden gängige Modellierungssprachen wie Ereignisgesteuerte Prozesskette, Business Process Model and Notation, Unified Modeling Language-Aktivitätsdiagramm und Petri-Netze erklärt. Die Anwendung dieser Sprachen wird anhand einer umfangreichen Sammlung von Aufgaben und Lösungen vertieft. Insbesondere unterstützen verschiedene Aufgabentypen (z. B. Modellierung, textuelle Beschreibungen, Multiple Choice Aufgaben und Fehlerfindung) die Intensivierung des Lernprozesses zu Modellierungssprachen. Neben der Modellierung von Geschäftsprozessen bietet das Buch ebenfalls sehr viele Aufgaben zur Analyse von Geschäftsprozessen, die sich thematisch mit Netztransformationen, strukturellen und dynamischen Eigenschaften, Erreichbarkeitsanalysen und Analysen basierend auf linearer Algebra beschäftigen. Schlagworte: Geschäftsprozesse; Modellierungssprachen; BPMN; EPK; Petri-Netz; Process Mining; Übungsaufgaben; Klausuraufgaben Andreas Drescher studierte Wirtschaftsingenieurwesen am Karlsruher Institut für Technologie (KIT). Die von ihm betreuten Übungen zu den Vorlesungen »Modellierung von Geschäftsprozessen« und »Workflow-Management« wurden mehrfach für gute Lehre ausgezeichnet. Agnes Koschmider vertritt eine Professur für Angewandte Informatik am Karlsruher Institut für Technologie (KIT). Zwischen den Jahren 2005 und 2015 war sie Dozentin und Übungsleiterin der Vorlesung »Workflow-Management« am KIT. Andreas Oberweis ist Professor für Betriebliche Informationssysteme am Karlsruher Institut für Technologie (KIT). Er ist Dozent für die beiden Vorlesungen »Modellierung von Geschäftsprozessen« und »Workflow-Management«.
eBook
The metaverse as a breakthrough for operations and supply chain management: implications and call for action
PurposeThe metaverse development is in the early stages in most organizations and supply chains. There has been exponential growth in metaverse investments by leading tech and other types of companies and governments worldwide. This article aims to shed light on the topic by providing detailed insights for the operations and supply chain management (O&SCM) community concerning the potential, opportunities and challenges associated with the metaverse.Design/methodology/approachThe authors mapped 15 benefits and 15 challenges regarding metaverse in O&SCM-related fields from the literature, which in turn were empirically tested by a panel with 150 experts from more than 12 countries, from operations and supply chains and with experience in metaverse technologies.FindingsThe authors found notable similarities and differences between metaverse adopters and non-adopters in the O&SCM. Accordingly, some benefits and challenges are expected before and after the implementation, but it's still relevant. In contrast, there are ones that change their importance after the implementation.Research limitations/implicationsFirst, this paper points out the need for an urgent call for action to develop high-quality research on the interplay between metaverse and O&SCM. Second, the metaverse will reshape several established business models by offering new products and services, consequently resulting in the remodeling of O&SCM. Third, our paper provides a call for action to engage the community of scholars and practitioners to consider the metaverse as one of the last frontiers of O&SCM in the digital age.Originality/valueThis paper is one of the first that investigates the metaverse benefits, challenges and expectations in the O&SCM. Also, it provides robust directions by an empirical approach to the metaverse as a new and important research stream for O&SCM and related fields. The authors provide a prospective research agenda that scholars and practitioners could use as a roadmap to capture metaverse opportunities in O&SCM.
Journal Article
External Knowledge and Information Technology
Prior information systems research highlights the vital role of information technology (IT) for innovation in firms. At the same time, innovation literature has shown that accessing and integrating knowledge from sources that reside outside the firm, such as customers, competitors, universities, or consultants, is critical to firms’ innovative success. In this paper, we draw on the knowledge-based view of the firm to investigate how search in external knowledge sources and information technology for knowledge absorption jointly influence process innovation performance. Our model is tested on a nine-year panel (2003–2011) of Swiss firms from a wide range of manufacturing industries. Using instrumental variables, and disaggregating by type of IT, we find that data access systems and network connectivity hold very different potential for the effective absorption of external knowledge, and the subsequent realized economic gains from process innovation. Against the backdrop of today’s digital transformation, our findings demonstrate how firms should coordinate strategies for sourcing external knowledge with specific IT investments in order to improve their innovation performance.
Journal Article
Impact of disruptions in agri-food supply chain due to COVID-19 pandemic: contextualised resilience framework to achieve operational excellence
PurposeThe present study aims to assess the role of supply chain resilience as an operational excellence approach to deal with disruptions caused by coronavirus pandemic in the food supply chain of an agri-food supply firm.Design/methodology/approachThe case study method was used to analyse the disruptions faced by the agricultural food supply chain during the pandemic. The study applies a dynamic capability theory as a foundation to develop a contextualised resilience framework for agri-food supply chain to achieve operational excellence. The case has been analysed by using situation-actor-process (SAP) and learning-action-performance (LAP) framework.FindingsThe SAP aspect of framework points that the flexibility amongst actors for a resilient agriculture supply chain worsened due to the lockdown measures post COVID-19. The LAP aspect of framework suggests how resilience can be built at the supply, demand and logistics end through various proactive and reactive practices such as collaboration, coordination, ICT and ground-level inputs. Lack of commitment and inadequate support from top management towards supply chain resilience are also observed as significant challenges to maintain operational excellence during the pandemic.Research limitations/implicationsOne of the major implications of the study is that a mix of capabilities rather than a single capability can be the most appropriate way for making the supply chain resilient to maintain operational excellence during the pandemic. However, the sources of disruptions need to be duly recognised to derive the best-contextualised resilience framework for agri-food supply chains.Originality/valueThe development of a contextualised research framework as well as research propositions for analysing supply chain resilience are the major contribution of this study.
Journal Article
Brilliance in resilience: operations and supply chain management’s role in achieving a sustainable future
PurposeThe purpose of this article is to discuss how the mastery of resilience in operations and supply chains plays a significant role in the transition to a more sustainable future. Furthermore, it is supposed to propose avenues for future research on operational and supply chain resilience, interacting with the sustainability literature in our field.Design/methodology/approachA conceptual review of resilience and sustainability themes within operations and supply chain management research is conducted. Reflections on the topic are informed by relevant literature published over the last decade.FindingsThe major conceptual contributions are threefold: (1) This article elaborates on the understanding of operational resilience and supply chain resilience concepts and reviews their respective primary research streams. (2) It proposes resilience as the missing element in the pursuit of excellence in organizations that want to contribute to a more sustainable future. (3) The article offers a research framework that provides a future research agenda at the intersection of resilience and sustainability in operations and supply chain management research.Originality/valueThe article highlights gaps in current research and illustrates further areas of research that need to be addressed to maximize the contribution of operations and supply chain management research in supporting practitioners to achieve a more sustainable future.
Journal Article
Comprehensible Predictive Models for Business Processes
Predictive modeling approaches in business process management provide a way to streamline operational business processes. For instance, they can warn decision makers about undesirable events that are likely to happen in the future, giving the decision maker an opportunity to intervene. The topic is gaining momentum in process mining, a field of research that has traditionally developed tools to discover business process models from data sets of past process behavior. Predictive modeling techniques are built on top of process-discovery algorithms. As these algorithms describe business process behavior using models of formal languages (e.g., Petri nets), strong language biases are necessary in order to generate models with the limited amounts of data included in the data set. Naturally, corresponding predictive modeling techniques reflect these biases. Based on theory from grammatical inference, a field of research that is concerned with inducing language models, we design a new predictive modeling technique based on weaker biases. Fitting a probabilistic model to a data set of past behavior makes it possible to predict how currently running process instances will behave in the future. To clarify how this technique works and to facilitate its adoption, we also design a way to visualize the probabilistic models. We assess the effectiveness of the technique in an experimental evaluation with synthetic and real-world data.
Journal Article