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Virtual reality (VR) is starting to realize some of its promise as a tool to improve training effectiveness. However, research on VR for training and development is limited. Existing theories and models relating to organizational training and learning are infrequently used in the VR literature. A greater understanding of why VR works in the training context would help training designers create effective programs that leverage this continuously developing technology. This paper provides a typology of VR technologies specifically relevant to HR and integrates HR training frameworks and theory into findings on VR training from these other literatures. We specifically focus on immersive VR technology and seek to better understand reasons for the effectiveness of VR technologies for both training and assessment. We review findings, integrate related streams of research, and offer guideposts for those contemplating VR implementation in four important areas: training reactions in a VR context, VR-specific learning outcomes, opportunities for assessment using VR, and the effect of VR on training transfer. We conclude the paper by identifying a VR-training agenda for HR researchers.
Towards an Omni-Channel Framework for SME Sales and Service in the B2B Telecommunications Industry
(2018)
Torsions- und Druckbelastung am Knick-Senkfuß mit und ohne sensomotorisch wirkender Fußorthese
(2018)
Synthesis and Luminescence of the New Ligand Exchanged Cluster Compound (n-Bu4N)2[Mo6I8(CH3SO3)6
(2018)
Focal companies are embedded in complex supply networks consisting of various suppliers, customers, competitors and complementors. The activities of these actors influence the com-petitive position of the focal companies. Some customers achieve preferred customer status and gain preferential treatment, others have to restrain to being standard customers getting less privileged services. Consequently, buying companies in such markets have to achieve transparency about the relationships of their suppliers towards their competitors and comple-mentors in order to map them and to analyse their impact. Current literature lacks a holistic approach to capture these relationships. In which sources can the focal companies find the desired information? Which kind of information do they really need? And in which situations is the need for transparency high and when is it low? The aim of this research is to examine these relationships using a World Café method with purchasers for data gathering followed by a Gioia method to structure the qualitative data. The result is a list of desired knowledge cov-ering business, supplier and collaboration details; a set of information sources clustered in pub-lished and unpublished sources as well as contingency factors regarding general conditions, changes and particular occasions that require a high supplier relationship knowledge. All an-swers have been rated by their importance during the World Café. The answers can help to operationalise the mapping of supplier relationships towards competitors and complementors in order to assess the own customer status compared to other customers.
Metal air batteries provide a high energy density as the ca-thodic reaction uses the surrounding air. Different metals can be usedbut zinc is very promising due to its disposability and nontoxic behav-ior. State estimation is quite complicated as the voltage characteristicof the battery is rather flat. Especially estimating the state of chargeis important as a secondary electrolysis process during overcharging canlead to an unsafe state. Another technique for state estimation is theelectrochemical impedance spectroscopy. Therefore, this paper describesthe process of setup and measuring a time series of impedance spectraat known states of charge. Then these spectra are used to derive anequivalent circuit. Finally the development of the circuit’s parameter areanalyzed to extract most important parameters.
The main task of battery management systems is to keep the working area of the battery in a safe state. Estimation of the state of charge and the state of health is therefore essential. The traditional way uses the voltage level of a battery to determine those values. Modern metal air batteries provide a flat voltage characteristic which necessitates new approaches. One promising technique is the electrochemical impedance spectroscopy, which measures the AC resistance for a set of different frequencies. Previous approaches match the measured impedances with a nonlinear equivalent circuit, which needs a lot of time to solve a nonlinear least-squares problem. This paper combines the electrochemical impedance spectroscopy with neural networks to speed up the state estimation using the example of zinc air batteries. Moreover, these networks are trained with different subsets of the spectra as input data in order to determine the required number of frequencies.
Spectral properties and thermal quenching of Mn4+ luminescence in multicomponent garnet hosts
(2018)
Without adequate measures, reservoirs are not sustainable, neither the
reservoir itself due to continuous sedimentation, nor the downstream ecosystem due to altered sediment continuity. Appropriate actions are inevitable and require a systematic sedimentation management. Sediment bypassing constitutes one effective strategy that routes sediment load around reservoirs during floods. A sediment bypass system has the advantage that only newly entrained sediment is diverted from the upstream to the downstream reach thereby re-establishing sediment connectivity. Hence, such a system contributes to a sustainable water resources management while taking the downstream environment into consideration. This paper gives a state-of-the-art overview
encompassing design, bypass efficiency, hydraulics, challenges due to abrasion, positive effects on both downstream morphology and ecology, and makes design recommendations.
In this paper typical bypass efficiencies of sediment bypass tunnels (SBTs) used to counter reservoir sedimentation are described, distinguishing between two layouts of the tunnel intake. It results that SBTs are an effective measure to reduce the sedimentation of dam reservoirs, particularly of type (A) with intake at the reservoir head. The hydroabrasive wear of tunnel inverts is significant and
has to be mitigated by using adequate invert liners. The invert abrasion can be estimated based on an abrasion model where a correct input value of the bed material resistance coefficient is paramount to limit model uncertainties. Based on abrasion measurements at prototype SBTs typical values of the material resistance coefficient are recommended for high-strength concrete, natural stones and steel liners. The field experiences gathered so far and the comparison of various invert materials suggest granite pavers as a promising lining material for severe abrasion conditions.
This paper describes the design of the new tunnel invert lining of the 9-foot tunnel at Mud Mountain Dam, Washington, USA. The tunnel diverts all bed load sediments into the tailwater. Major invert abrasion has been observed in the existing steel lining. The new invert design consists of 0.59 m2 and 0.79 m2 granite blocks that are 0.25 m thick and placed tightly together along the tunnel. Stability analysis showed factors of safety ranging from 1.2 to 2.6 against uplift. This will be achieved with strip drains placed in the bedding material along the tunnel. A service-design-life analysis was performed using abrasion prediction modelling.
This model was based on abrasion measurement data acquired from granite field tests at Pfaffensprung sediment bypass tunnel, Switzerland. The estimated annual abrasion depths for the granite were approximately 0.50 mm/year for average sediment transport conditions.
Nonlocal quantum kinetic theory and dynamical constraints on phase transitions in the early universe
(2018)
The paper deals with the development of a new type of production planning and control in a wood-processing company. The production is already highly automated and data from the production processes are gathered and stored in a database. The project picks up these technical basements in order to automatically provide intelligent decisions and make the factory even smarter.
Globalization, digitalization and increasingly shortened lifecycles of consumer and business goods require companies to be continuously innovative. Under these domains of innovation, disruptive innovation has developed as a popular term amongst scholars and practitioners alike (Christensen, Raynor, & McDonald, 2015). In fact, the concept of disruptive technolo-gies was introduced to explain the failure of incumbent businesses in times of change (Bower & Christensen, 1995). Later, research broadened the concept towards disruptive innovations thereby going beyond technologies alone (Yu & Hang, 2010). Indeed, recent literature stresses the embracing business model that needs to be designed appropriately to make use of the technology and push it forward in the process of disruption. Subse-quently, current research concludes that disruption in its core is a “business model problem, not a technology problem” (Christensen, 2006).
Despite the recognition of the relevance of a firm’s business model for disruption, a clarifi-cation of the business model concept in the disruptive innovation process appears to be necessary in two dimensions. First, there is only limited knowledge regarding the actual design of (potential) disruptive business models. Second, from a dynamic perspective, less is known about how organizations manage the process of disruptive innovation until their business model yields a disruptive effect in the market.
The PhD research project aims at shedding light on the role of the firm’s business model in regard to the concept of disruptive innovation. Insights from this research project will not only add to a deeper understanding of disruptive innovation from a theoretical perspective but also deliver guidance for managers facing an increasingly changing environment.