Customer attractiveness, supplier satisfaction and preferred customer status: a review and a cycle model

In this paper, we introduce the concept of preferred customer status, i.e. a buyer is awarded preferential treatment of its important suppliers compared to their other customers. As there is a lack of knowledge of what motivates suppliers to serve selected buyers better than others, our research focuses on the suppliers’ evaluation of customers and how it can be influenced by buyers. Based on social exchange theory, we provide a conceptual model which proposes customer attractiveness, supplier satisfaction and knowledge of alternative customers as factors influencing suppliers to award preferred customer status. Subsequently, a literature review is provided to give an overview of the drivers of customer attractiveness, supplier satisfaction and preferred customer status already analysed in current literature. We conclude by providing a preliminary conceptual framework and suggesting future research directions in this field. This article proposes new insights into supplier relationship management and offers a state-of-the-art analysis as well as a theoretical base to this new research field

Industry 4.0 and how purchasing can progress and benefit from the fourth industrial revolution

Since its’ announcement in 2011, the number of scientific publications on Industry 4.0 is growing exponentially. Significant investments by industrial firms, at present and planned for the coming years, indicate the expectations by the industry in terms of increased productivity because of the fourth industrial revolution. However, the link between purchasing and Industry 4.0 is largely lacking in scientific literature, despite the high financial impact of procurement for organizations. The fourth industrial revolution – cyber-physical systems with autonomous machine-to-machine communication – could enable several possibilities for purchasing. On the one hand support systems for purchasers are conceived, such as contract analysis software. On the other hand, the scenario of digital negotiations emerges, which could revitalize e- marketplaces. Operative processes can act autonomously, with automated demand identification in cyber-physical systems. In order to support the development of I4.0 strategies in purchasing, this paper further contributes by presenting the result of a project on developing a specific purchasing I4.0 maturity model

{PoseTrackReID}: {D}ataset Description

Current datasets for video-based person re-identification (re-ID) do not include structural knowledge in form of human pose annotations for the persons of interest. Nonetheless, pose information is very helpful to disentangle useful feature information from background or occlusion noise. Especially real-world scenarios, such as surveillance, contain a lot of occlusions in human crowds or by obstacles. On the other hand, video-based person re-ID can benefit other tasks such as multi-person pose tracking in terms of robust feature matching. For that reason, we present PoseTrackReID, a large-scale dataset for multi-person pose tracking and video-based person re-ID. With PoseTrackReID, we want to bridge the gap between person re-ID and multi-person pose tracking. Additionally, this dataset provides a good benchmark for current state-of-the-art methods on multi-frame person re-ID

Discovering Class-Specific GAN Controls for Semantic Image Synthesis

Prior work has extensively studied the latent space structure of GANs forunconditional image synthesis, enabling global editing of generated images bythe unsupervised discovery of interpretable latent directions. However, thediscovery of latent directions for conditional GANs for semantic imagesynthesis (SIS) has remained unexplored. In this work, we specifically focus onaddressing this gap. We propose a novel optimization method for findingspatially disentangled class-specific directions in the latent space ofpretrained SIS models. We show that the latent directions found by our methodcan effectively control the local appearance of semantic classes, e.g.,changing their internal structure, texture or color independently from eachother. Visual inspection and quantitative evaluation of the discovered GANcontrols on various datasets demonstrate that our method discovers a diverseset of unique and semantically meaningful latent directions for class-specificedits.<br

Prognos (R) in the diagnosis of amalgam hypersensitivity - A diagnostic case-control study

Objective: We aimed to investigate whether the Prognos (R) device might be a useful tool in the diagnosis of disorders suspected to be due to dental amalgam fillings. Participants and Methods: A diagnostic case-control study was performed in 27 patients who complained about health problems attributed to amalgam ( cases), 27 healthy volunteers with amalgam fillings ( controls I), and 27 healthy amalgam-free volunteers ( controls II). All participants were tested before and after application of 300 mg DMPS (2.3-dimercapto-1-propanesulfonic acid) with Prognos, a diagnostic device for the energetic measurement of Traditional Chinese Medicine meridians. In addition, mercury was measured in blood, urine, and saliva, and a lymphocyte transformation test (LTT) was performed. Results: Diagnoses derived from the first and second Prognos testing did not agree above chance (Cohen's Kappa = -0.11, 95% confidence interval -0.33 to 0.10; p = 0.30). Agreement for secondary outcome measures was poor, too. Prognos measurements did not differ between cases and controls. Correlations with measurements in urine, blood and saliva were low. Conclusion: In this study Prognos could not be shown to be a useful tool in the diagnosis of disorders suspected to be due to dental amalgam fillings