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The coupling of the heat and power sector is required as supply and demand in the German electricity mix drift further and further apart with a high percentage of renewable energy. Heat pumps in combination with thermal energy storage systems can be a useful way to couple the heat and power sectors. This paper presents a hardware-in the-loop test bench for experimental investigation of optimized control strategies for heat pumps. 24-hour experiments are carried out to test whether the heat pump is able to serve optimized schedules generated by a MATLAB algorithm. The results show that the heat pump is capable of following the generated schedules, and the maximum deviation of the operational time between schedule and experiment is only 3%. Additionally, the system can serve the demand for space heating and DHW at any time.
A distinctive highlight of the dissertation at hand is the investigation of multiple apparel supply chain actors incorporating the views of a global apparel retailer in Europe and multiple suppliers in Vietnam and Indonesia.
More specifically, the dissertation presents a coherent investigation starting with the depiction of a conceptual framework for social management strategies as a means for social risk management (SRM), exclusively aiming at the apparel industry. In accordance to the identified research gaps and suggested research directions from the conceptual framework, the role of the apparel sourcing agent for social management strategies was analysed by conducting a multiple case study approach with evidence from Vietnam and Europe, ultimately suggesting ten propositions. Whereas a further multiple case study data collection in Vietnam, Indonesia and Europe allowed for the investigation of buyer-supplier relationships with regards to social compliance strategies by using core tenets of agency theory to interpret the findings and outline ten propositions. Based on the development of a conceptual framework on social SSCM in the apparel industry, the formulation of related 20 propositions with evidence from crucial developing (apparel sourcing) countries, and the application of agency theory which has been declared as a shortfall in this context, this thesis contributes with further grounding to SSCM theory and substantially contributes to the debate by addressing numerous research gaps.
A large body of literature is concerned with models of presence— the sensory illusion of being part of a virtual scene— but there is still no general agreement on how to measure it objectively and reliably. For the presented study, we applied contemporary theory to measure presence in virtual reality. Thirty-seven participants explored an existing commercial game in order to complete a collection task. Two startle events were naturally embedded in the game progression to evoke physical reactions and head tracking data was collected in response to these events. Subjective presence was recorded using a post-study questionnaire and real-time assessments. Our novel implementation of behavioral measures lead to insights which could inform future presence research: We propose a measure in which startle reflexes are evoked through specific events in the virtual environment, and head tracking data is compared to the range and speed of baseline interactions.
In recent years, the parallel computing community has shown increasing interest in leveraging cloud resources for executing parallel applications. Clouds exhibit several fundamental features of economic value, like on-demand resource provisioning and a pay-per-use model. Additionally, several cloud providers offer their resources with significant discounts; however, possessing limited availability. Such volatile resources are an auspicious opportunity to reduce the costs arising from computations, thus achieving higher cost efficiency. In this paper, we propose a cost model for quantifying the monetary costs of executing parallel applications in cloud environments, leveraging volatile resources. Using this cost model, one is able to determine a configuration of a cloud-based parallel system that minimizes the total costs of executing an application.
Mystery shopping (MS) is a widely used tool to monitor the quality of service and personal selling. In consultative retail settings, assessments of mystery shoppers are supposed to capture the most relevant aspects of sales people’s service and sales behavior. Given the important conclusions drawn by managers from MS results, the standard assumption seems to be that assessments of mystery shoppers are strongly related to customer satisfaction and sales performance. However, surprisingly scant empirical evidence supports this assumption. We test the relationship between MS assessments and customer evaluations and sales performance with large-scale data from three service retail chains. Surprisingly, we do not find asubstantial correlation. The results show that mystery shoppers are not good proxies for real customers. While MS assessments are not related to sales, our findings confirm the established correlation between customer satisfaction measurements and sales results.
In this paper we describe an interactive web-based visual analysis tool for Formula one races. It first provides an overview about all races on a yearly basis in a calendar-like representation. From this starting point, races can be selected and visually inspected in detail. We support a dynamic race position diagram as well as a more detailed lap times line plot for showing the drivers’ lap times in comparison. Many interaction techniques are supported like selections, filtering, highlighting, color coding, or details-on demand. We illustrate the usefulness of our visualization tool by applying it to a Formula one dataset while we describe the different dynamic visual racing patterns for a number of selected races and drivers.
Polyurethane-bases block copolymers (TPCUs) are block-copolymers with systematically varied soft and hard segments. They have been suggested to serve as material for chondral implants in joint regeneration. Such applications may require the adhesion of chondrocytes to the implant surface, facilitating cell growth while keeping their phenotype. Thus, aims of this work were (1) to modify the surface of soft biostable polyurethane-based model implants (TPCU and TSiPCU) with high-molecular weight hyaluronic acid (HA) using an optimized multistep strategy of immobilization, and (2) to evaluate bioactivity of the modified TPCUs in vitro. Our results show no cytotoxic potential of the TPCUs. HAbioactive molecules (Mw =700kDa) were immobilized onto the polyurethane surface via polyethylenimine (PEI) spacers, and modifications were confirmed by several characterization methods. Tests with porcine chondrocytes indicated the potential of the TPCU-HA for inducing enhanced cell proliferation.
Purpose – The purpose of this paper is to examine the mediating effect of psychological contract breach on the relationship between job insecurity and counterproductive workplace behavior (CWB) and the moderating effect of employment status in this relationship.
Design/methodology/approach – Data were collected from 212 supervisor–subordinate dyads in a large Chinese state-owned air transportation group. AMOS 17.0 software was used to examine the hypothesized predictions and the theoretical model.
Findings – The results showed that psychological contract breach partially mediates the effect of job insecurity on CWB, including organizational counterproductive workplace behavior and interpersonal counterproductive workplace behavior. In addition, the relationships between job insecurity, psychological contract breach and CWB differ significantly between permanent workers and contract workers.
Originality/value – The present study provides a new insight into explaining the linkage between job insecurity and negative work behaviors as well as suggestions to managers on minimizing the harmful effects of job insecurity.
Organisationslernen
(2019)
Durch Organisationslernen passen sich Organisationen an veränderte Umweltanforderungen (Digitalisierung, politische Reformen, usw.) an. Organisationen können die Lernfähigkeit erhöhen, indem sie ihre dynamischen Fähigkeiten durch eine geringe Arbeitsteilung stärken, ihren Absorptionsprozess von Wissen hinterfragen, und strukturelle und zeitliche Ambidextrie schaffen. Sie können sich am Leitbild der lernenden Organisation orientieren und flache Organisationsstrukturen sowie Teamarbeit fördern. Insbesondere für öffentliche Verwaltungen, die derzeit nicht ausreichend lernfähig sind, bietet das Organisationslernen sinnvolle Ansatzpunkte.
Data analytics tasks on large datasets are computationally intensive and often demand the compute power of cluster environments. Yet, data cleansing, preparation, dataset characterization and statistics or metrics computation steps are frequent. These are mostly performed ad hoc, in an explorative manner and mandate low response times. But, such steps are I/O intensive and typically very slow due to low data locality, inadequate interfaces and abstractions along the stack. These typically result in prohibitively expensive scans of the full dataset and transformations on interface boundaries.
In this paper, we examine R as analytical tool, managing large persistent datasets in Ceph, a wide-spread cluster file-system. We propose nativeNDP – a framework for Near Data Processing that pushes down primitive R tasks and executes them in-situ, directly within the storage device of a cluster-node. Across a range of data sizes, we show that nativeNDP is more than an order of magnitude faster than other pushdown alternatives.