Nein
Refine
Document Type
- Journal article (706)
- Conference proceeding (659)
- Book chapter (367)
- Book (133)
- Anthology (36)
- Doctoral Thesis (31)
- Patent / Standard / Guidelines (24)
- Working Paper (9)
- Report (3)
- Review (3)
Is part of the Bibliography
- yes (1973)
Institute
- ESB Business School (541)
- Informatik (484)
- Technik (405)
- NXT Nachhaltigkeit und Technologie (197)
- Life Sciences (188)
- Texoversum (148)
- Zentrale Einrichtungen (7)
Publisher
- Springer (457)
- IEEE (274)
- Elsevier (116)
- VDE Verlag (57)
- Association for Computing Machinery (51)
- Wiley (48)
- Erich Schmidt Verlag (40)
- Association for Information Systems (25)
- De Gruyter (25)
- Emerald (25)
This study explores the potential role of virtual influencers in future B2B marketing. Combining expert interviews and a literature review, the findings reveal the growing popularity of virtual influencers due to Web 3.0 and Metaverse advancements. The study suggests that virtual influencers may revolutionize brand-customer interactions in the digital space, with implications for B2B marketing strategies.
Downtimes (outages) are unfavorable and costly events in production. Although approaches exist, they have to be implemented mainly manually and with a huge effort. Language models could be useful to support the production root cause failure analysis and help to get production up and running again more quickly. However, sparse research focused on this point so far. Therefore, it is still unclear how the usage of language models for human assistance in production failure root case analysis should be implemented. A qualitative expert study was conducted to reveal the potentials of such an approach and to find suitable use cases for language models. Based on the insights triggering factors, use cases as well as benefits and risks were identified and summarized within a model.
Recent research has suggested that there is no general similarity measure, which can be applied on arbitrary databases without any parameterization. Hence, the optimal combination of similarity measures and parameters must be identified for each new image repository. This optimization loop is time consuming and depends on the experience of the designer as well as the knowledge of the medical expert. It would be useful if results that have been obtained for one data set can be transferred to another without extensive re-design. This transfer is vital if content-based image retrieval is integrated into complex environments such as picture archiving and communication systems. The image retrieval in medical applications (IRMA) project defines a framework that strictly separates data administration and application logic. This permits an efficient transfer of the data abstraction of one database on another without re-designing the software. In the ImageCLEF competition, the query performance was evaluated on the CasImage data set without optimization of the feature combination successfully applied to the IRMA corpus. IRMA only makes use of basic features obtained from grey-value representations of the images without additional textual annotations. The results indicate that transfer of parameterization is possible without time consuming parameter adaption and significant loss of retrieval quality.
This article analyzes the Korean innovation system and presents suggestions for its further improvement on the basis of three other country models, that of the U.S., Japan and Germany. We suggest that innovation systems are embedded in their respective managerial, economic, socio-political, and ultimately cultural context and that those contextual factors exert a significant influence on a national innovation system. Furthermore, we propose that the influence of those contextual factors result in innovation systems that are either more transformational or incremental in nature. We conclude that Korea has (like Japan) due to its societal context a particular strength in incremental innovations but will increasingly need to build up its ability to generate also transformational innovations (a particular strength of the US model). Due to distinct differences in the societal context, it might be difficult, however, for Korea to follow the U.S. model. We suggest, therefore, that Korea might find some valuable lessons in the German innovation system, particularly regarding small and medium enterprises.
The ImageCLEF 2006 medical automatic annotation task encompasses 11,000 images from 116 categories, compared to 57 categories for 10,000 images of the similar task in 2005. As a baseline for comparison, a run using the same classifiers with the identical parameterization as in 2005 is submitted. In addition, the parameterization of the classifier was optimized according to the 9,000/1,000 split of the 2006 training data. In particular, texture-based classifiers are combined in parallel with classifiers, which use spatial intensity information to model common variabilities among medical images. However, all individual classifiers are based on global features, i.e. one feature vector describes the entire image. The parameterization from 2005 yields an error rate of 21.7%, which ranks 13th among the 28 submissions. The optimized classifier yields 21.4% error rate (rank 12), which is insignificantly better.
China ist inzwischen Deutschlands Exportpartner Nummer acht. Im Vertrieb vieler Unternehmen wird neu gelernt, dass man das Vertrauen chinesischer Kunden nicht wie in Deutschland gewinnt. Der Erfahrungsschatz von Relationship Managern, die auf dem chinesischen Markt erfolgreich sind, kann dabei sehr hilfreich sein.
Brasilien gehört zu den aufstrebenden Wachstumsmärkten der Welt. Vieles spricht dafür, dass der größte Staat Südamerikas zu den wirtschaftlichen und politischen Führungsmächten der Zukunft zählt. Ein Grund mehr für deutsche Unternehmen, sich um ein erfolgreiches Management der Beziehungen zu brasilianischen Kunden zu kümmern.
The objective of this article is to take a closer look at discourse analysis as a qualitative method of data collection, analysis and theory building in Human Resource Management. Working exclusively with audio or video recordings of authentic conversations and following a systematic methodological process, discourse analysis enables researchers to develop theoretical conclusions and models on HR topics. First, basic assumptions and tools of discourse analysis are presented. Special emphasis is put on the applied discourse analytical approach and potential benefits for research on Human Resource Management. Second, drawing on a research project carried out at the University of Bayreuth, an example is presented of how discourse analysis was used to investigate experience management. The project yielded a theoretical model that describes the communicative processes of experience transfer among expatriate managers. It reveals the particular challenges involved as well as strategies interactants use to cope with them. Being strictly action-oriented, the model is advantageous for deducing recommendations for Human Resource Development.
Spätestens seit Verbreitung der Thesen zur Wissensschaffung von Nonaka und Takeuchi in den 90er Jahren haben Unternehmen die enorme Bedeutung impliziten Wissens erkannt. Sie bemühen sich zunehmend, den Austausch von Erfahrungswissen unter Mitarbeitern zu fördern. Ziel ist es, dieses in der Organisation zu bewahren und strategisch zu nutzen. Allerdings gibt es bisher kaum Konzepte für die praktische Umsetzung eines Erfahrungsmanagements im Unternehmen. Welche Kontexte sind für die Erfahrungsweitergabe Erfolg versprechend? Und wie kann dabei implizites Wissen in explizites umgewandelt werden?
