Mapping domain characteristics influencing Analytics initiatives: The example of Supply Chain Analytics

Purpose: Analytics research is increasingly divided by the domains Analytics is applied to. Literature offers little understanding whether aspects such as success factors, barriers and management of Analytics must be investigated domain-specific, while the execution of Analytics initiatives is similar across domains and similar issues occur. This article investigates characteristics of the execution of Analytics initiatives that are distinct in domains and can guide future research collaboration and focus. The research was conducted on the example of Logistics and Supply Chain Management and the respective domain-specific Analytics subfield of Supply Chain Analytics. The field of Logistics and Supply Chain Management has been recognized as early adopter of Analytics but has retracted to a midfield position comparing different domains. Design/methodology/approach: This research uses Grounded Theory based on 12 semi-structured Interviews creating a map of domain characteristics based of the paradigm scheme of Strauss and Corbin. Findings: A total of 34 characteristics of Analytics initiatives that distinguish domains in the execution of initiatives were identified, which are mapped and explained. As a blueprint for further research, the domain-specifics of Logistics and Supply Chain Management are presented and discussed. Originality/value: The results of this research stimulates cross domain research on Analytics issues and prompt research on the identified characteristics with broader understanding of the impact on Analytics initiatives. The also describe the status-quo of Analytics. Further, results help managers control the environment of initiatives and design more successful initiatives.DFG, 414044773, Open Access Publizieren 2019 - 2020 / Technische Universität Berli

Overcoming Barriers in Supply Chain Analytics—Investigating Measures in LSCM Organizations

While supply chain analytics shows promise regarding value, benefits, and increase in performance for logistics and supply chain management (LSCM) organizations, those organizations are often either reluctant to invest or unable to achieve the returns they aspire to. This article systematically explores the barriers LSCM organizations experience in employing supply chain analytics that contribute to such reluctance and unachieved returns and measures to overcome these barriers. This article therefore aims to systemize the barriers and measures and allocate measures to barriers in order to provide organizations with directions on how to cope with their individual barriers. By using Grounded Theory through 12 in-depth interviews and Q-Methodology to synthesize the intended results, this article derives core categories for the barriers and measures, and their impacts and relationships are mapped based on empirical evidence from various actors along the supply chain. Resultingly, the article presents the core categories of barriers and measures, including their effect on different phases of the analytics solutions life cycle, the explanation of these effects, and accompanying examples. Finally, to address the intended aim of providing directions to organizations, the article provides recommendations for overcoming the identified barriers in organizations

Explaining the competitive advantage generated from Analytics with the knowledge-based view: the example of Logistics and Supply Chain Management

The purpose of this paper is to provide a theory-based explanation for the generation of competitive advantage from Analytics and to examine this explanation with evidence from confirmatory case studies. A theoretical argumentation for achieving sustainable competitive advantage from knowledge unfolding in the knowledge-based view forms the foundation for this explanation. Literature about the process of Analytics initiatives, surrounding factors, and conditions, and benefits from Analytics are mapped onto the knowledge-based view to derive propositions. Eight confirmatory case studies of organizations mature in Analytics were collected, focused on Logistics and Supply Chain Management. A theoretical framework explaining the creation of competitive advantage from Analytics is derived and presented with an extensive description and rationale. This highlights various aspects outside of the analytical methods contributing to impactful and successful Analytics initiatives. Thereby, the relevance of a problem focus and iterative solving of the problem, especially with incorporation of user feedback, is justified and compared to other approaches. Regarding expertise, the advantage of cross-functional teams over data scientist centric initiatives is discussed, as well as modes and reasons of incorporating external expertise. Regarding the deployment of Analytics solutions, the importance of consumability, users assuming responsibility of incorporating solutions into their processes, and an innovation promoting culture (as opposed to a data-driven culture) are described and rationalized. Further, this study presents a practical manifestation of the knowledge-based view

Shallow BF2 implants in Xe-bombardment-preamorphized Si: the interaction between Xe and F

Si(100) samples, preamorphized to a depth of ~30 nm using 20 keV Xe ions to a nominal fluence of 2×1014 cm-2 were implanted with 1 and 3 keV BF2 ions to fluences of 7×1014 cm-2. Following annealing over a range of temperatures (from 600 to 1130 °C) and times the implant redistribution was investigated using medium-energy ion scattering (MEIS), secondary ion mass spectrometry (SIMS), and energy filtered transmission electron microscopy (EFTEM). MEIS studies showed that for all annealing conditions leading to solid phase epitaxial regrowth, approximately half of the Xe had accumulated at depths of 7 nm for the 1 keV and at 13 nm for the 3 keV BF2 implant. These depths correspond to the end of range of the B and F within the amorphous Si. SIMS showed that in the preamorphized samples, approximately 10% of the F migrates into the bulk and is trapped at the same depths in a ~1:1 ratio to Xe. These observations indicate an interaction between the Xe and F implants and a damage structure that becomes a trapping site. A small fraction of the implanted B is also trapped at this depth. EXTEM micrographs suggest the development of Xe agglomerates at the depths determined by MEIS. The effect is interpreted in terms of the formation of a volume defect structure within the amorphized Si, leading to F stabilized Xe agglomerates or XeF precipitates

Two cases of variceal haemorrhage during living-donor liver transplantation

Some patients with cirrhosis experience rupture of venous varices before operation, and liver transplantation is a therapy of last resort for these patients. However, we have experienced two cases of intraoperative rupture in whom no abnormalities of the venous varices were seen on endoscopy before operation. One patient with ruptured gastrointestinal varices was treated by direct surgical ligation and the other with ruptured oesophageal gastric varices, spontaneously recovered with a Sengstaken–Blakemore tube. These cases suggest that acute variceal haemorrhage should always be considered as a possibility during living-donor liver transplantation in patients with a history of upper gastrointestinal bleeding. Careful observation of the nasogastic tube is important during clamping of the hepatic portal vein

Normally preordered spaces and utilities

In applications it is useful to know whether a topological preordered space is normally preordered. It is proved that every $k_\omega$-space equipped with a closed preorder is a normally preordered space. Furthermore, it is proved that second countable regularly preordered spaces are perfectly normally preordered and admit a countable utility representation.Comment: 17 pages, 1 figure. v2 contains a second proof to the main theorem with respect to the published version. The last section of v1 is not present in v2. It will be included in a different wor

Open questions in utility theory

Throughout this paper, our main idea is to explore different classical questions arising in Utility Theory, with a particular attention to those that lean on numerical representations of preference orderings. We intend to present a survey of open questions in that discipline, also showing the state-of-art of the corresponding literature.This work is partially supported by the research projects ECO2015-65031-R, MTM2015-63608-P (MINECO/ AEI-FEDER, UE), and TIN2016-77356-P (MINECO/ AEI-FEDER, UE)