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This paper studies whether a monetary union needs a fical union in particular in the Eurozone. On 1 January 1999, despite controversial debates, the rule-based Economic and Monetary Union (EMU) started without a fiscal union. I show that there is weak economic convergence in the EMU since 18 years. In addition, I argue that a fiscal union does not solve the past disintegration failures.
I demonstrate that the major flaws are domestic policy failures and not institutional failures in the euro area. Consequently, establishing a monetary union without having a political union is a risky strategy. Indeed, the rule-based architecture of Maastricht is not guilty for the crisis alone. The root causes are the political flaws aligned with the rather weak enforcement of the rules. I propose a genuine redesign of the rule-based paradigm without a fiscal union. Yet a monetary union without a fiscal union works effectively if the rule enforcement is more automatic and independent of domestic and European policy-making.
The high system flexibility necessary for the full automation of complex and unstructured tasks leads to increased complexity, thus higher costs. On the other hand, the effectiveness and performance of such systems decrease, explaining the unfulfilled potential of robotcs in sectors such as intralogistics, where the benefits of a robotic solution rarely justify its costs. Taking the distance from the false idea that a task should be either fully automated, or fully manual, this aper presents a method for design of a lean human-robot interaction (HRI) withe the objective of the "right level of automation", where functions are divided among human and automated agends, so that the overall process gains in performances and/or costs. ... The 10 progressive steps of the method are presented and discussed with reference to their graphical tool: the House of Quality Interaction.
Successful digital business strategies rely less on strategic analysis and big bets than on experiments and learning. Consider, for example, that Airbnb grew out of the belief that people would pay to sleep on air mattress on a stranger's floor. Similarly, Instagram started as an app for checking in and hanging out with friends (and sharing pictures) that proved complicated to use. Twitter's founders had first tried a podcasting platform, Odeo, which Apple made obsolete with iTunes. AUDI AG had to kill of its "share a car with five friends" app before rolling out more successful mobility services in a number of countries. The digital successes did not grow out of a comprehensive upfront analysis. Digital strategy emerges from an idea - often, not a particularly good idea.
In recent years the share economy has gained widespread success across different industries. Since small firms and new ventures obtain fewer resources, an increased focus on service allows them to differentiate and compete with cost pressure in traditionally manufacturing based industries. There still is a lack of understanding how these firms manage to successfully shift towards service-oriented business models. This paper adopts a dynamic capabilities approach to examine the particular microfoundations that underlie sensing, seizing and reconfiguring dynamic capabilities of early-stage service firms within a traditional retail market. The context of this study is the fashion industry. It is an ideal setting since it is characterized by severe competition, short life cycles, strong cost pressure and high volatility. There are few but increasing examples of entrepreneurial initiatives that try to compete by providing offers to resell, rent or swap clothes. Qualitative data of five early stage fashion ventures is analyzed. Findings reveal that the ability to develop and maintain long-term relationships is essential. It has also been found crucial to acquire knowledge from external network partners, delegate tasks and share information. Furthermore, skills for interacting with customers and adopting consumer feedback are critical. This study provides empirical evidence of dynamic capabilities of early-stage firms and contributes to knowledge on the factors that facilitate servitization in traditionally manufacturing based industries. For practitioners, the presented microfoundations provide a framework of critical tasks that allow them to develop and maintain a service oriented business model.
After considering significant literature on sustainable supply chain management (SSCM), it is evident that research has neglected the social dimension and still lacks in highlighting the role of sourcing intermediaries in supply chains. The apparel supply chain has increased enormously in length and complexity, driving apparel retailers to employ sourcing intermediaries who manage their sourcing activities with suppliers from developing countries overseas. Thus, the purpose of this study is to enrich existing findings on SSCM by exploring the management of social sustainability when sourcing intermediaries are in between the focal company and the respective developing country factories. More specifically, this study aims to understand the role of apparel sourcing intermediaries for the implementation of social management strategies based on the perception of multiple supply chain actors. Qualitative data was collected through semi-structured interviews conducted in Vietnam and Europe. Ultimately ten propositions are presented, all explicitly concentrating on the apparel intermediary’s role as a significant enabler for social sustainability in apparel supply chains. The roles are social sustainability, supplier developer and coordinator, gatekeeper and safeguard, cultural broker, and social risk manager. The social sustainability roles assumed by the apparel sourcing intermediary offer great opportunities to both apparel retailers and developing country factories.
Strategy to test mobile apps
(2014)
Nowadays the development of a mobile app implies challenges and difficulties, which have to be faced by mobile app developers. Innovations lead to a rapidly evolving mobile app market, therefore apps should be developed faster and offered in short release cycles to the market. Testing is a decisive activity within the development process that helps to improve the quality of the app. This research paper describes a strategy to test mobile apps that overcomes the challenges that mobile apps confront and permits to test the app in a structural test environment.
Motor-based theories of facial expression recognition propose that the visual perception of facial expression is aided by sensorimotor processes that are also used for the production of the same expression. Accordingly, sensorimotor and visual processes should provide congruent emotional information about a facial expression. Here, we report evidence that challenges this view. Specifically, the repeated execution of facial expressions has the opposite effect on the recognition of a subsequent facial expression than the repeated viewing of facial expressions. Moreover, the findings of the motor condition, but not of the visual condition, were correlated with a nonsensory condition in which participants imagined an emotional situation. These results can be well accounted for by the idea that facial expression recognition is not always mediated by motor processes but can also be recognized on visual information alone.
A fully passive RFID temperature sensor SoC with an accuracy of ±0.4°C (3σ) from 0°C to 125°C
(2018)
This paper presents a fully passive 13.56 MHz RFID temperature sensor system-on-chip. Its power management unit (PMU) operates over a large temperature range using a zero temperature coefficient (TC) bias source. On-chip temperature sensing is accomplished with low voltage, low power CMOS circuitry and time-domain signal processing. Two operating modes have been defined to study supply noise sensitivity: command mode and listening mode, which represent sensor operation during RFID command transfer and listening, respectively. Besides a standard readout command, a customized serial readout command is utilized to distinguish the data from both modes. In command mode, the sensor suffers from interference from the RFID command packet and outputs interference as well, while the sensor outputs no interference in listening mode. Measurements show that sensor resolution in listening mode is improved by a factor of approximately 16 compared to command mode. The chip was fabricated in a standard 0.35 µm CMOS technology and chip-on-board mounted to a tuned RFID transponder coil on an aluminium core FRA4 PCB substrate. Real-time wireless temperature sensing has been demonstrated with a commercial HF RFID reader. With a two-point calibration, the SoC achiesves a 3σ sensing accuracy of ±0.4°C from 0° C to 125° C.
Micro grids often consist of energy generators, storages and consumers with controllers which are not prepared for their integration into communication networks for energy systems. In this paper it will be presented, how standards from the field of energy automation can be applied in such controllers. The data for communication interfaces can be structured according to the IEC 61850- or the VHPREADY standard. It is investigated which requirements must be supported to implement such data models within the controllers. For the transmission of the data we propose the OPC UA protocol, which supports extensive security measures and which is today available for nearly all modern types of controllers and computers.
For autonomously driving cars and intelligent vehicles it is crucial to understand the scene context including objects in the surrounding. A fundamental technique accomplishing this is scene labeling. That is, assigning a semantic class to each pixel in a scene image. This task is commonly tackled quite well by fully convolutional neural networks (FCN). Crucial factors are a small model size and a low execution time. This work presents the first method that exploits depth cues together with confidence estimates in a CNN. To this end, novel experimentally grounded network architecture is proposed to perform robust scene labeling that does not require costly preprocessing like CRFs or LSTMs as commonly used in related work. The effectiveness of this approach is demonstrated in an extensive evaluation on a challenging real-world dataset. The new architecture is highly optimized for high accuracy and low execution time.
