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Real estate markets are known to fluctuate. The real estate market in Stuttgart, Germany, has been booming for more than a decade: square-meter price hit top levels and real estate agents claim that market prices will continue to increase. In this paper, we test this market understanding by developing and analyzing a system dynamics model that depicts the Stuttgart real estate market. Simulating the model explains oscillating behavior arising from significant time delays and endogenous feedback structures – and not necessarily oscillating interest rates, as market experts assume. Scenarios provide insights into the system's behavior reacting to changes exogenous to the model. The first scenario tests the market development under increasing interest rates. The other scenario deals with possible effects on the real estate market if the regional automotive economy suffers from intense competition with new market players entering with alternative fuel vehicles and new technologies. With a policy run we test market structure changes to eliminate cyclical effects. The paper confirms that the business cycle in the Stuttgart real estate market arises from within the system's underlying structure, thus emphasizing the importance of understanding feedback structures.
Decreasing batch sizes in production in line with Industrie 4.0 will lead to tremendous changes of the control of logistic processes in future production systems. Intelligent bins are crucial enablers to establish decentrally controlled material flow systems in value chain networks as well as at the intralogistics level. These intelligent bins have to be integrated into an overall decentralized monitoring and control approach and have to interact with humans and other entities just like other cyber-physical systems (CPS) within the cyber-physical production system (CPPS). To realize a decentralized material supply following the overall aim of a decentralized control of all production and logistics processes, an intelligent bin system is currently developed at the ESB Logistics Learning Factory. This intelligent bin system will be integrated into the self developed, cloud-based and event-oriented SES system (so-called “Self Execution System”) which goes beyond the common functionalities and capabilities of traditional manufacturing execution systems (MES).
To ensure a holistic integration of the intelligent bin for different material types into the SES framework, the required hard- and software components for the decentrally controlled bin system will be split into a common and an adaptable component. The common component represents the localization and network layer which is common for every bin, whereas the flexible component will be customizable to different requirements, like to the specific characteristics of the parts.
It is assumed that more education leads to better understanding of complex systems. Some researchers, however, find indications that simple mechanisms like stocks and flows are not well understood even by people who have passed higher education. In this paper, we test people’s understanding of complex systems with the widely studied stock-and-flow (SF) tasks. SF tasks assess people’s understanding of the interplay between stocks and flows. We investigate SF failure of domain experts and novices in different knowledge domains. In particular, we compare performance on the original study’s bathtub task with the square wave pattern with two alternative cover stories from the engineering and business domains on different groups of business and engineering students from different semesters. Further, we show that, while engineering students perform better than business students, with progressing in higher education, students may lose the capability of dealing with simple SF tasks. We thus find hints on déformation professionelle in higher education.
Close and safe interaction of humans and robots in joint production environments is technically feasible, however should not be implemented as an end in itself but to deliver improvement in any of a production system’s target dimensions. Firstly, this paper shows that an essential challenge for system integrators during the design of HRC applications is to identify a suitable distribution of available tasks between a robotic and a human resource. Secondly, it proposes an approach to determine task allocation by considering the actual capabilities of both human and robot in order to improve work quality. It matches those capabilities with given requirements of a certain task in order to identify the maximum congruence as the basis for the allocation decision. The approach is based on a study and subsequent generic description of human and robotic capabilities as well as a heuristic procedure that facilities the decision making process.
Curriculum design for the German language class in the double-degree programme business engineering
(2017)
This paper aims to give an overview on how German is taught as a foreign language to students enrolled in the Bachelor of Business Engineering, a double-degree programme offered in Universiti Malaysia Pahang. The double degree students have the opportunity to complete their first two years of study in Malaysia and their last two years in Germany. Taking the TestDaF examination is compulsory for double-degree students. Hence, the German Language curriculum has been meticulously planned to ensure the students would be competent in the language. As such, the settings of the language class are discussed thoroughly in this paper. Additionally, it also discusses the challenges faced in teaching German as foreign language. This paper ends with some suggestions for improvement.
The modern industrial corporation encompasses a myriad of different software applications, each of which must work in concert to deliver functionality to end-users. However, the increasingly complex and dynamic nature of competition in today’s product-markets dictates that this software portfolio be continually evolved and adapted, in order to meet new business challenges. This ability – to rapidly update, improve, remove, replace, and reimagine the software applications that underpin a firm’s competitive position – is at the heart of what has been called IT agility. Unfortunately, little work has examined the antecedents of IT agility, with respect to the choices a firm makes when designing its “Software Portfolio Architecture.”
We address this gap in the literature by exploring the relationship between software portfolio architecture and IT agility at the level of the individual applications in the architecture. In particular, we draw from modular systems theory to develop a series of hypotheses about how different types of coupling impact the ability to update, remove or replace the software applications in a firm’s portfolio. We test our hypotheses using longitudinal data from a large financial services firm, comprising over 1,000 applications and over 3,000 dependencies between them. Our methods allow us to disentangle the effects of different types and levels of coupling.
Our analysis reveals that applications with higher levels of coupling cost more to update, are harder to remove, and are harder to replace, than those with lower coupling. The measures of coupling that best explain differences in IT agility include all indirect dependencies between software applications (i.e., they include coupling and dependency relationships that are not easily visible to the system architect). Our results reveal the critical importance of software portfolio design decisions, in developing a portfolio of applications that can evolve and adapt over time.
Technologies for mapping the “digital twin“ have been under development for approximately 20 years. Nowadays increasingly intelligent, individualized products encourages companies to respond innovatively to customer requirements and to handle the rising product variations quickly.
An integrated engineering network, spanning across the entire value chain, is operated to intelligently connect various company divisions, and to generate a business ecosystem for products, services and communities. The conditions for the digital twin are thereby determined in which the digital world can be fed into the real, and the real world back into the digital to deal such intelligent products with rising variations.
The term digital twin can be described as a digital copy of a real factory, machine, worker etc., that is created and can be independently expanded, automatically updated as well as being globally available in real time. Every real product and production site is permanently accompanied by a digital twin. First prototypes of such digital twins already exist in the ESB Logistics Learning Factory on a cloud- and app based software that builds on a dynamic, multidimensional data and information model. A standardized language of the robot control systems via software agents and positioning systems has to be integrated. The aspect of the continuity of the real factory in the digital factory as an economical means of ensuring continuous actuality of digital models looks as the basis of changeability.
For the indoor localization sensor combinations that in addition to the hardware already contain the software required for the sensor data fusion should be used. Processing systems, scenario-live-simulations and digital shop floor management results in a mandatory procedural combination. Essential to the digital twin is the ability to consistently provide all subsystems with the latest state of all required information, methods and algorithms.
Digitization will require companies to fundamentally reengineer their sales processes. Adapting the concept of value selling to the digital age will enable them to deliver superior value to their customers. Specifically, social selling will provide them with an answer to the ever-increasing complexity of customer journeys. This article, based on a survey among 235 German companies, assesses the status quo and outlines opportunities. Moreover, it introduces a novel approach for developing well-grounded social selling metrics.
Recent digital technologies like the Internet of Things and Augmented Reality have brought IT into companies’ core products. What were previously purely physical products are becoming hybrid or digitized. Despite receiving a lot of recent attention, digitized products have only seen a slow uptake in businesses so far. In this paper, we study the challenges that keep companies from realizing the desired impacts of digitized products and the practices they employ to address these challenges. To do so, we looked at companies from a set of industries that are highly affected by digital transformation, but at the same time hesitant to move to a more digitized world: the creative industries. Based on a literature review and twelve interviews in creative industries, we developed a conceptual model that can serve as a basis for formulating testable hypotheses for further research in this area.
The purpose of this paper is to study the impact of transparency on the political budget cycle (PBC) over time and across countries. So far, the literature on electoral cycles finds evidence that cycles depend on the stage of an economy. However, the author shows – for the first time – a reliance of the budget cycle on transparency. The author uses a new data set consisting of 99 developing and 34 Organization for Economic Cooperation and Development countries. First, the author develops a model and demonstrates that transparency mitigates the political cycles. Second, the author confirms the proposition through the econometric assessment. The author uses time series data from 1970 to 2014 and discovers smaller cycles in countries with higher transparency, especially G8 countries.