Article
Refine
Year of publication
Institute
- Fachbereich Wirtschaftswissenschaften (116) (remove)
Language
- English (116) (remove)
Document Type
- Article (116) (remove)
Keywords
- rebound-effect (2)
- sustainability (2)
- Bank-issued Warrants (1)
- Brands (1)
- Centrifugal twisting moment (1)
- Change (1)
- Charging station (1)
- Clinical decision support systems (1)
- Consensus (1)
- Discourse ethics (1)
The presented paper gives an overview of the most important and most common theories and concepts from the economic field of organisational change and is also enriched with quantitative publication data, which underlines the relevance of the topic. In particular, the topic presented is interwoven in an interdisciplinary way with economic psychological models, which are underpinned within the models with content from leading scholars in the field. The pace of change in companies is accelerating, as is technological change in our society. Adaptations of the corporate structure, but also of management techniques and tasks, are therefore indispensable. This includes not only the right approaches to employee motivation, but also the correct use of intrinsic and extrinsic motivational factors. Based on the hypothesis put forward by the scientist and researcher Rollinson in his book “Organisational behaviour and analysis” that managers believe motivational resources are available at all times, socio-economic and economic psychological theories are contrasted here in order to critically examine this statement. In addition, a fictitious company was created as a model for this work in order to illustrate the effects of motivational deficits in practice. In this context, the theories presented are applied to concrete problems within the model and conclusions are drawn about their influence and applicability. This led to the conclusion that motivation is a very individual challenge for each employee, which requires adapted and personalised approaches. On the other hand, the recommendations for action for supervisors in the case of motivation deficits also cannot be answered in a blanket manner, but can only be solved with the help of professional, expert-supported processing due to the economic-psychological realities of motivation. Identifying, analysing and remedying individual employee motivation deficits is, according to the authors, a problem and a challenge of great importance, especially in the context of rapidly changing ecosystems in modern companies, as motivation also influences other factors such as individual productivity. The authors therefore conclude that good motivation through the individual and customised promotion and further training of employees is an important point for achieving important corporate goals in order to remain competitive on the one hand and to create a productive and pleasant working environment on the other.
Knowledge-based productivity in “low-tech” industries: evidence from firms in developing countries
(2014)
Using firm-level data from five developing countries—Brazil, Ecuador, South Africa, Tanzania, and Bangladesh—and three industries—food processing, textiles, and the garments and leather products—this article examines the importance of various sources of knowledge for explaining productivity and formally tests whether sector- or country-specific characteristics dominate these relationships. Knowledge sources driving productivity appear mainly sector specific. Also differences in the level of development affect the effectiveness of knowledge sources. In the food processing sector, firms with higher educated managers are more productive, and in least-developed countries, additionally those with technology licenses and imported machinery and equipment. In the capital-intensive textiles sector, productivity is higher in firms that conduct R&D. In the garments and leather products sector, higher education of the managers, licensing, and R&D raise productivity.
Knowledge Management
(2001)
Providing healthcare services frequently involves cognitively demanding tasks, including diagnoses and analyses as well as complex decisions about treatments and therapy. From a global perspective, ethically significant inequalities exist between regions where the expert knowledge required for these tasks is scarce or abundant. One possible strategy to diminish such inequalities and increase healthcare opportunities in expert-scarce settings is to provide healthcare solutions involving digital technologies that do not necessarily require the presence of a human expert, e.g., in the form of artificial intelligent decision-support systems (AI-DSS). Such algorithmic decision-making, however, is mostly developed in resource- and expert-abundant settings to support healthcare experts in their work. As a practical consequence, the normative standards and requirements for such algorithmic decision-making in healthcare require the technology to be at least as explainable as the decisions made by the experts themselves. The goal of providing healthcare in settings where resources and expertise are scarce might come with a normative pull to lower the normative standards of using digital technologies in order to provide at least some healthcare in the first place. We scrutinize this tendency to lower standards in particular settings from a normative perspective, distinguish between different types of absolute and relative, local and global standards of explainability, and conclude by defending an ambitious and practicable standard of local relative explainability.
IT Service Deployment
(2007)
In this article, we introduce how eye-tracking technology might become a promising tool to teach programming skills, such as debugging with ‘Eye Movement Modeling Examples’ (EMME). EMME are tutorial videos that visualize an expert's (e.g., a programming teacher's) eye movements during task performance to guide students’ attention, e.g., as a moving dot or circle. We first introduce the general idea behind the EMME method and present studies that showed first promising results regarding the benefits of EMME to support programming education. However, we argue that the instructional design of EMME varies notably across them, as evidence-based guidelines on how to create effective EMME are often lacking. As an example, we present our ongoing research on the effects of different ways to instruct the EMME model prior to video creation. Finally, we highlight open questions for future investigations that could help improving the design of EMME for (programming) education.
Info-Web-Generation
(2004)
Today’s society is undergoing a paradigm shift driven by the megatrend of sustainability. This undeniably affects all areas of Western life. This paper aims to find out how the luxury industry is dealing with this change and what adjustments are made by the companies. For this purpose, interviews were conducted with managers from the luxury industry, in which they were asked about specific measures taken by their companies as well as trends in the industry. In a subsequent evaluation, the trends in the luxury industry were summarized for the areas of ecological, social, and economic sustainability. It was found that the area of environmental sustainability is significantly more focused than the other sub-areas. Furthermore, the need for a customer survey to validate the industry-based measures was identified.
We introduce a new way to measure the forecast effort that analysts devote to their earnings forecasts by measuring the analyst's general effort for all covered firms. While the commonly applied effort measure is based on analyst behaviour for one firm, our measure considers analyst behaviour for all covered firms. Our general effort measure captures additional information about analyst effort and thus can identify accurate forecasts. We emphasise the importance of investigating analyst behaviour in a larger context and argue that analysts who generally devote substantial forecast effort are also likely to devote substantial effort to a specific firm, even if this effort might not be captured by a firm-specific measure. Empirical results reveal that analysts who devote higher general forecast effort issue more accurate forecasts. Additional investigations show that analysts' career prospects improve with higher general forecast effort. Our measure improves on existing methods as it has higher explanatory power regarding differences in forecast accuracy than the commonly applied effort measure. Additionally, it can address research questions that cannot be examined with a firm-specific measure. It provides a simple but comprehensive way to identify accurate analysts.