Refine
Year
Publication Type
- Article (1300)
- Lecture (866)
- Conference Proceeding (564)
- Part of a Book (530)
- Book (128)
- Report (65)
- Bachelor Thesis (28)
- Master's Thesis (23)
- Contribution to a Periodical (21)
- Participation in a Norm (DIN, RFC etc.) (12)
Language
- English (3543) (remove)
Has Fulltext
- no (3543) (remove)
Keywords
- Humans (15)
- Child (13)
- Female (12)
- Male (12)
- Urban (11)
- Adolescent (10)
- Adult (10)
- Wohnraum (9)
- Middle Aged (8)
- Surveys and Questionnaires (7)
Faculty
- Chemieingenieurwesen (CIW) (722)
- Wirtschaft (MSB) (711)
- Physikingenieurwesen (PHY) (484)
- Oecotrophologie · Facility Management (OEF) (316)
- Sozialwesen (SW) (220)
- Energie · Gebäude · Umwelt (EGU) (188)
- Elektrotechnik und Informatik (ETI) (187)
- Gesundheit (MDH) (155)
- Maschinenbau (MB) (151)
- Bauingenieurwesen (BAU) (128)
Family firm performance through transformational CEO leadership and familiness-related team forces
(2024)
Purpose. The purpose of this study is to test the role of familiness-related team forces induced by the CEO of family firms. In particular, we report on the effects of the transformational leadership style of CEOs on their respective top-management team (TMT) and firm performance when viewed through a familiness lens.
Design/methodology/approach. Survey measures were taken from a snowballed
sample of 72 CEOs of German family firms as well as from 245 members of their TMTs. We tested the aggregated firm-level data with objective performance indicators of the firms they led.
Findings. Support was obtained for the three hypothesized team-force mediations and the four-path mediation model. The relationship between CEO’s transformational style and
high family-firm performance is found to be serially mediated by TMT cohesion, behavioral integration and efficacy. Together, these three types of collective forces are assumed to be the
familiness effect of a family-member CEO with a transformational leadership style.
Originality. With our model we quantitatively tested familiness-type forces vis-à-vis firm performance. Theoretical and practical implications of these findings are discussed.
Supply chains often match the supply of labour to uncertain demand by using precarious workprecarious workers. This increases flexibility and lowers costs for the supply chain by shifting risk to the workers and costs to society. Supply chains are maximizing profits, often literally, on the backs of their workers by creating serious negative externalities for society. We address this issue using a powerpower perspective because powerpower is asymmetrically oriented against workers in many supply chain contexts. This allows us to identify examples of how to reverse this trend and shift powerpower back to workers. The goal is to get to where stakeholders understand the costs and limited benefits of precarity, where we can separate the notion of flexibility from low costs, and where through a combination of incentives, policy, social norms of ethical behaviour, and consumer action, we can get to a better place than where we are now.
An important, often overlooked group of workers that HR managers have trouble reaching are those intentionally disconnected from personal digital devices. That is, workers in manufacturing facilities, distribution centers, secure areas, or locations where employers ban workers from bringing their own devices. We explore the engagement problem for these intentionally disconnected workers. We outline a disruptive HR strategy in these work contexts. We then focus on implementation, testing a simple digital platform prototype that can serve as an entry for existing, disruptive HR management engagement tools (e.g. chatbots, HR analytics) in these settings. Our exploratory findings suggest engagement is a problem for these workers and these simple tools can be an effective strategy to help HR managers improve engagement. We conclude that simple digital solutions aimed at engaging this underserved segment of the workforce can have disruptive yet positive effects for workers, HR managers and shareholders.
In-depth analysis of customer journeys to broaden the understanding of customer behaviors and expectations in order to improve the customer experience is considered highly relevant in modern business practices. Recent studies predominantly focus on retrospective analysis of customer data, whereas more forward-directed concepts, namely predictions, are rarely addressed. Additionally, the integration of robotic process automation (RPA) to potentially increase the efficiency of customer journey analysis is not discussed in the current field of research. To fill this research gap, this paper introduces “customer journey mining”. Process mining techniques are applied to leverage digital customer data for accurate prediction of customer movements through individual journeys, creating valuable insights for improving the customer experience. Striving for improved efficiency, the potential interplay of RPA and customer journey mining is examined accordingly. The research methodology followed is based on a design science research process. An initially defined customer journey mining artifact is operationalized through an illustrative case study. This operationalization is achieved by analyzing a log file of an online travel agency functioning as an orientation for researchers and practitioners while also evaluating the initially defined framework. The data is used to train seven distinct prediction models to forecast the touchpoint a customer is most likely to visit next. Gradient-boosted trees yield the highest prediction accuracy with 43.1%. The findings further indicate technical suitability for RPA implementation, while financial viability is unlikely.
Against the setting of an increasing need for innovation and low margins, companies in the logistics
sector are facing highly competitive pressure. One field with high potential for optimization lies within
damage quotas. The use of big data analytics or data mining represents a promising approach to face
this challenge. However, within supply chain management, data mining is hardly being researched on
regarding damage quotas and thus not being utilized to its full possible extend. At the current time it
seems to predominantly be used for route and utilization optimization while the analysis of delivery
damages is hardly considered.
The aim of this research is therefore to showcase an initial approach for data mining in logistics to predict
delivery damage probabilities and to validate this by means of a multiple case study research. To create
a sound basis for evaluation, the groundwork is laid out based on CRISP-DM by the analysis of reference
data (German road-cargo market).
As a central result it is noted that data mining can systematically be used to help reducing the damages
by forecasting the probabilities of damages occurring during transport in dependence of different factors.
The approach can be utilized across different markets as long as sufficient data tracking delivery
damages is being collected within a company. Challenges arise in the field of air- and sea-freight.
A novel approach for ventilation systems is a periodically varying supply air flow rate, the so-called unsteady mode of operation. So far, useful effects of this unsteady operating mode have been observed, but the effect mechanisms are still unknown. In this manuscript, simulations using the recently proposed k-ω-ζ - f model implemented in a sensitized RANS computational framework for a cuboid room with swirl diffusers are compared and validated with PIV measurements.
This article explores educational media pedagogies that are predominantly non-digital, but nonetheless timely and influential. Design Thinking, Making, and Serious Play are three distinct yet interrelated approaches to problem-solving, resilience and innovation that have gained increased traction in education over the past decade. We explore the similarities and differences between these playful, experiental pedagogies and provide an overview of how these approaches can be integrated effectively into education settings. Finally, we provide transferable examples, including evaluation results, from a weeklong workshop series at Muenster University of Applied Sciences conducted in Spring 2022. The article serves as a theoretically informed practical guide for educators and practitioners seeking to select, implement and evaluate playful pedagogies. It contributes to the understanding of underlying principles, characteristics, potential impact and limitations.
Wastewater Generation Model to Predict Impacts of Urine Separation on Wastewater Treatment Plants
(2023)
Wastewater treatment plants are under increasing pressure to enhance resource efficiency and reduce emissions into water bodies. Separation of urine within the catchment area may be an alternative to mitigate the need for costly expansions of central wastewater treatment plant. While previous investigations assumed a spatially uniform implementation of urine separation across the catchment area, the present study introduces a modelling framework which allows to determine the influence of targeted urine separation on the operation and emissions of central wastewater treatment plants. The framework includes an adapted stochastic wastewater generation model, the Stormwater Management Model, and Activated Sludge Model No. 3 with Bio-P module (SIMBA#). The entire application is embedded in the R programming language. The model is validated by an extensive sampling and measurement campaign. Preliminary results based on observed and simulated wastewater generation and transport for a catchment area of 436 residents indicate the suitability of the model for wastewater generation and transport modelling, but also show further need for calibration.
Objective:
We examined whether autonomic flexibility to experimentally presented stressors is reduced in somatic symptom disorder (SSD) as this would point to reduced vagal control as a proposed indicator of emotion regulation deficits.
Method:
In this experimental study, the influence of health-related and social stressors on subjective and physiological reactivity was investigated in 29 subjects with SSD without any medical condition SSD(mc−), 33 subjects with SSD with medical condition SSD(mc+) and 32 healthy controls at the age from 18 to 70 years. Self-report and physiological variables were measured before and after/during stressor exposure, using state ratings of symptom intensity, disability, tension and mood, heart rate (HR), and heart rate variability (HRV).
Results:
Overall, the tension increased and the mood worsened after exposure to stressors compared to pre-exposure. Compared to HC, the two SSD groups showed higher symptom intensity, disability, tension and worse mood. The SSD(mc−) group revealed higher HR than HC (p = .012, d = −0.77). Compared to pre-exposure, symptom impairment increased after social stressor exposure in SSD(mc−) (p < .001, d = 1.36). HRV-root mean square of successive differences (RMSSD) only decreased in HC during exposure (p = .003, d = −1.09), not in the SSD groups. The two SSD groups did not differ in their reactivity to stressors.
Conclusion:
HRV in SSD, seems to respond less flexibly to stressors, potentially reflecting overall physiological disturbance through reduced parasympathetic influence on HR. Stress reactivity in SSD(mc−) and SSD(mc+) do not seem to differ.
Additive manufacturing (AM) has been growing continuously over the past 20 years, enabling unprecedented tailoring to the anatomy of each patient. In Europe, custom-made devices qualify for an exemption and pass a simplified approval process. New technologies, like AM, provoke questions about the adequacy of the current regulatory framework for custom-made devices. This article addresses the regulatory requirements for such devices in Europe and discusses the implications for AM. It concludes that the legal framework for custom-made devices entails uncertainties which need to be resolved to guide manufacturers through the regulatory requirements, highlighting the specific areas of focus for AM.
Additive manufacturing (AM) has continuously grown in recent decades. Enhanced quality, further development of technology, and fall in prices make AM applicable and capable for various industrial applications, also for the manufacture of medical devices. 3D printing offers the possibility for an unprecedented adaptation to the anatomy of each patient, generating medical devices on a case-by-case basis. In many jurisdictions, custom-made devices qualify for an exemption to pre-market approval standards. This regulation is called into question by new technologies, like AM. Therefore, this article compares the current regulatory requirements for custom-made devices in Europe, the United States, and Australia and discusses the impact on 3D printed devices. It concludes that not all jurisdictions have yet adjusted their regulatory framework for custom-made devices to technological advances. Remaining uncertainties must be eliminated in order to help manufacturers comply with the regulatory requirements, emphasizing key aspects of AM.
Mobile health apps (MHAs) and medical apps (MAs) are becoming increasingly popular as digital interventions in a wide range of health-related applications in almost all sectors of healthcare. The surge in demand for digital medical solutions has been accelerated by the need for new diagnostic and therapeutic methods in the current coronavirus disease 2019 pandemic. This also applies to clinical practice in gastroenterology, which has, in many respects, undergone a recent digital transformation with numerous consequences that will impact patients and health care professionals in the near future. MHAs and MAs are considered to have great potential, especially for chronic diseases, as they can support the self-management of patients in many ways. Despite the great potential associated with the application of MHAs and MAs in gastroenterology and health care in general, there are numerous challenges to be met in the future, including both the ethical and legal aspects of applying this technology. The aim of this article is to provide an overview of the current status of MHA and MA use in the field of gastroenterology, describe the future perspectives in this field and point out some of the challenges that need to be addressed.