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Will chatbots play a significant role for B2B marketingin the future? Chatbots in B2B businesses
(2022)
Digitalization has gained a foothold in our everyday lives. However, it remains to be seen what digital tools B2B companies can benefit from. During the last few years, chatbots have been on the rise and have played a more significant role in B2B marketing. Thus, this research follows a literature review to examine the current state of B2B chatbots. With this, the study will discover the buyer’s preferences for chatbots compared to sales agents and the role of chatbots in different stages of the B2B sales funnel.
Die Debatte über die Zukunft der Europäischen Wirtschafts- und Währungsunion ist seit geraumer Zeit omnipräsent (Herzog und Hengstermann 2013). Mit der temporären Aussetzung der europäischen (nationalen) Schuldenregeln bis zum 31. Dezember 2022 ging abermals eine leidenschaftlich geführte Post-Covid-19-Reformdiskussion los. Zu den bisherigen Veränderungsnotwendigkeiten kommen nunmehr die geopolitischen Herausforderungen hinzu. Ist die Stabilität der Währungsunion in Gefahr?
Gamification erfährt seit Jahren zunehmende Aufmerksamkeit in Wissenschaft und Praxis. Eine 2019 veröffentliche Metaanalyse zur Gamification-Forschung zeigt, dass der Fokus bislang auf den Bereichen Bildung und Gesundheit lag. Mit verbreiteter Anwendung steigt allerdings der Bedarf, die Forschung auf weitere Felder auszuweiten. Dieser Beitrag ergründet die Potenziale von Gamification im B-to-B-Vertrieb. Eine Betrachtung an dieser Stelle eignet sich aus den folgenden Gründen: Gamification wird vor allem für diejenigen Felder als attraktiv bezeichnet, wo Aktivitäten komplex und vielfältig sind und Fortschritt nur schwer nachzuvollziehen ist. Darüber hinaus unterstützt Gamification in der Erzielung nachhaltiger Ergebnisse mit Kontinuität und langfristigem Engagement.
The implementation of human resource (HR) policies often proves troublesome due to the appearance, and stubborn persistence, of gaps in the process. Human resource management (HRM) scholars problematise these gaps and advocate tight implementation to reduce gaps and to ensure the desired impact of policies on organisational performance. Drawing on organisational institutionalism, we contend that gaps in implementing HR policies can actually be productive, as they secure organisational legitimacy, and thus enable organisations to operate viably within several institutional environments. We suggest that different approaches to implementation are needed, some of them premised on accepting sustained implementation gaps. We introduce minimum and moderate implementation approaches, rooted in the notion of decoupling, to complement approaches aimed at tight implementation. Our aim is to support the further development of research based on a richer interpretation of HRM implementation challenges and choices they present for HR managers.
In order to evaluate the performance of different stapes prosthesis types, a coupled finite element (FE) model of human ear was developed. First, the middle-ear FE model was developed and validated using the middle-ear transfer function measurements available in literature including pathological cases. Then, the inner-ear FE model was developed and validated using tonotopy, impedance, and level of cochlea amplification curves from literature. Both models are based on pre-existing research with some improvements and were combined into one coupled FE model. The stapes in the coupled FE ear model was replaced with a model of a stapes prosthesis to create a reconstructed ear model that can be used to estimate how different types of protheses perform relative to each other as well as to the natural ear. This will help in designing of new innovative types of stapes prostheses or any other type of middle-ear prostheses as well as to improve the ones that are already available on the market.
Ultra wideband real-time locating system for tracking people and devices in the operating room
(2022)
Position tracking within the OR could be one possible input for intraoperative situation recognition. Our approach demonstrates a Real-time Locating System (RTLS) using the Ultra Wideband (UWB) technology to determine the position of people or objects. The UWB RTLS was integrated into the research OR at Reutlingen University and the system’s settings were optimized regarding the four factors accuracy, susceptibility to interference, range, and latency. Therefore, different parameters were adapted and the effects on the factors were compared. Goodtracking quality could be achieved under optimal settings. These results indicate that a UWB RTLS is well suited to determine the position of people and devices in our setting. The feasibility of the system needsto be evaluated under real OR conditions.
Turning students into Industry 4.0 entrepreneurs: design and evaluation of a tailored study program
(2022)
Startups in the field of Industry 4.0 could be a huge driver of innovation for many industry sectors such as manufacturing. However, there is a lack of education programs to ensure a sufficient number of well-trained founders and thus a supply of such startups. Therefore, this study presents the design, implementation, and evaluation of a university course tailored to the characteristics of Industry 4.0 entrepreneurship. Educational design-based research was applied with a focus on content and teaching concept. The study program was first implemented in 2021 at a German university of applied sciences with 25 students, of which 22 participated in the evaluation. The evaluation of the study program was conducted with a pretest–posttest-design targeting three areas: (1) knowledge about the application domain, (2) entrepreneurial intention and (3) psychological characteristics. The entrepreneurial intention was measured based on the theory of planned behavior. For measuring psychological characteristics, personality traits associated with entrepreneurship were used. Considering the study context and the limited external validity of the study, the following can be identified in particular: The results show that a university course can improve participants' knowledge of this particular area. In addition, perceived behavioral control of starting an Industry 4.0 startup was enhanced. However, the results showed no significant effects on psychological characteristics.
The food system represents a key industry for Europe and Germany in particular. However, it is also the single most significant contributor to climate and environmental change. A food system transformation is necessary to overcome the system’s major and constantly increasing challenges in the upcoming decades. One possible facilitator for this transformation are radical and disruptive innovations that start-ups develop. There are many challenges for start-ups in general and food start-ups in particular. Various support opportunities and resources are crucial to ensure the success of food start-ups. One aim of this study is to identify how the success of start-ups in the food system can be supported and further strengthened by actors in the innovation ecosystem in Germany. There is still room for improvement and collaboration toward a thriving innovation ecosystem. A successful innovation ecosystem is characterised by a well-organised, collaborative, and supportive environment with a vivid exchange between the members in the ecosystem. The interviewees confirmed this, and although the different actors are already cooperating, there is still room for improvement. The most common recommendation for improving cooperation is learning from other countries and bringing the best to Germany.
Industrial practice is characterized by random events, also referred to as internal and external turbulences, which disturb the target-oriented planning and execution of production and logistics processes. Methods of probabilistic forecasting, in contrast to single value predictions, allow an estimation of the probability of various future outcomes of a random variable in the form of a probability density function instead of predicting the probability of a specific single outcome. Probabilistic forecasting methods, which are embedded into the analytics process to gain insights for the future based on historical data, therefore offer great potential for incorporating uncertainty into planning and control in industrial environments. In order to familiarize students with these potentials, a training module on the application of probabilistic forecasting methods in production and intralogistics was developed in the learning factory 'Werk150' of the ESB Business School (Reutlingen University). The theoretical introduction to the topic of analytics, probabilistic forecasting methods and the transition to the application domain of intralogistics is done based on examples from other disciplines such as weather forecasting and energy consumption forecasting. In addition, data sets of the learning factory are used to familiarize the students with the steps of the analytics process in a practice-oriented manner. After this, the students are given the task of identifying the influencing factors and required information to capture intralogistics turbulences based on defined turbulence scenarios (e.g. failure of a logistical resource) in the learning factory. Within practical production scenario runs, the students apply probabilistic forecasting using and comparing different probabilistic forecasting methods. The graduate training module allows the students to experience the potentials of using probabilistic forecasting methods to improve production and intralogistics processes in context with turbulences and to build up corresponding professional and methodological competencies.
With the progress of technology in modern hospitals, an intelligent perioperative situation recognition will gain more relevance due to its potential to substantially improve surgical workflows by providing situation knowledge in real-time. Such knowledge can be extracted from image data by machine learning techniques but poses a privacy threat to the staff’s and patients’ personal data. De-identification is a possible solution for removing visual sensitive information. In this work, we developed a YOLO v3 based prototype to detect sensitive areas in the image in real-time. These are then deidentified using common image obfuscation techniques. Our approach shows that it is principle suitable for de-identifying sensitive data in OR images and contributes to a privacyrespectful way of processing in the context of situation recognition in the OR.