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In order to determine demand as precisely as possible, many businesses use several forecasting methods. The aim of forecasting is to determine future demand based on data from the past. The use of a specific method is not always easy and depends on a number of factors. To help prospective engineers find the most suitable forecasting method for a specific problem, a forecasting game was developed and then evaluated.
The paper describes the design and the evaluation of the forecasting game. In order to provide an overview of existing forecasting methods, the first part of the paper examined the mathematical fundamentals of eight different forecasting methods and outlined the requirements for their application.
The second part of the paper describes the creation of a forecasting game in which prospective engineers can learn how to determine the appropriate forecasting method for specific scenarios. In total, five scenarios covering the three different demand patterns (linear/stationary, trend and seasonal) as well as the forecast quality methods were developed and can be played through. For each scenario, the player has to choose the most appropriate forecasting method for a specific problem based on a self-created task description. To make the game as realistic as possible, a fictional company with a background story was designed.
The last part was about the evaluation of the forecasting game. For the evaluation, a student survey to gather the opinions of the students was conducted. The results of the student survey show an overall positive evaluation of the simulation game by the students. However, the test also showed that the game takes a certain amount of time. Since only 15 of the approximately 30 students who tested the game participated in the evaluation, the results are not significant.
Management des Innovationsportfolios: Portfolio-Matrizen zumManagement von Innovationsprojekten
(2021)
The links between innovativeness as a driver of economic performance, and the determinants of innovativeness have been investigated by management scholars and economists for decades, focusing mostly on “hard factors” as investment in research and development, or education. Focusing on a relatively neglected, but in times of globalization even more important aspect, the infuence of cultural characteristics on innovativeness, we apply diferent econometric models to test for links between cultural tightness and looseness on the one hand, and national innovativeness on the other hand. We fnd that cultural tightness—in the sense of homogenous and intolerant societies—has a negative link to national innovativeness, while cultural looseness—in the sense of tolerant and diverse societies—displays a positive link to national innovativeness.
Von Maschinenbau-Ingenieur*innen wird oft erwartet, innovative Produkte, Dienstleistungen oder Prozesse zu entwickeln und zu vermarkten. Das Ziel der vorliegenden Arbeit ist es herauszufinden, inwiefern sie bereits im Masterstudium Maschinenbau durch die Förderung von Kreativität und Entrepreneurship darauf vorbereitet werden. Um die Forschungsfrage zu beantworten, wurden die Modulhandbücher der zehn größten Universitäten sowie Fachhochschulen mithilfe einer Schlagwortsuche auf einschlägige Begriffe analysiert. Die Studie zeigt, dass deutsche Ingenieur*innen sowohl an Fachhochschulen als auch an Universitäten hinsichtlich Kreativität und Entrepreneurship eher unzureichend ausgebildet werden.