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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.
Current clinical practice is often unable to identify the causes of conductive hearing loss in the middle ear with sufficient certainty without exploratory surgery. Besides the large uncertainties due to interindividual variances, only partially understood cause–effect principles are a major reason for the hesitant use of objective methods such as wideband tympanometry in diagnosis, despite their high sensitivity to pathological changes. For a better understanding of objective metrics of the middle ear, this study presents a model that can be used to reproduce characteristic changes in metrics of the middle ear by altering local physical model parameters linked to the anatomical causes of a pathology. A finite-element model is, therefore, fitted with an adaptive parameter identification algorithm to results of a temporal bone study with stepwise and systematically prepared pathologies. The fitted model is able to reproduce well the measured quantities reflectance, impedance, umbo and stapes transfer function for normal ears and ears with otosclerosis, malleus fixation, and disarticulation. In addition to a good representation of the characteristic influences of the pathologies in the measured quantities, a clear assignment of identified model parameters and pathologies consistent with previous studies is achieved. The identification results highlight the importance of the local stiffness and damping values in the middle ear for correct mapping of pathological characteristics and address the challenges of limited measurement data and wide parameter ranges from the literature. The great sensitivity of the model with respect to pathologies indicates a high potential for application in model-based diagnosis.
The scoring of sleep stages is an essential part of sleep studies. The main objective of this research is to provide an algorithm for the automatic classification of sleep stages using signals that may be obtained in a non-obtrusive way. After reviewing the relevant research, the authors selected a multinomial logistic regression as the basis for their approach. Several parameters were derived from movement and breathing signals, and their combinations were investigated to develop an accurate and stable algorithm. The algorithm was implemented to produce successful results: the accuracy of the recognition of Wake/NREM/REM stages is equal to 73%, with Cohen's kappa of 0.44 for the analyzed 19324 sleep epochs of 30 seconds each. This approach has the advantage of using the only movement and breathing signals, which can be recorded with less effort than heart or brainwave signals, and requiring only four derived parameters for the calculations. Therefore, the new system is a significant improvement for non-obtrusive sleep stage identification compared to existing approaches.
Due to its availability and minimal invasive harvesting human adipose tissue-derived extracellular matrix (dECM) is often used as a biomaterial in various tissue engineering and healthcare applications. Next to dECM, cell-derived ECM (cdECM) can be generated by and isolated from in vitro cultured cells. So far both types of ECM were investigated extensively toward their application as (bio)material in tissue engineering and healthcare. However, a systematic characterization and comparison of soft tissue dECM and cdECM is still missing. In this study, we characterized dECM from human adipose tissue, as well as cdECM from human adipose-derived stem cells, toward their molecular composition, structural characteristics, and biological purity. The dECM was found to exhibit higher levels of collagens and lower levels of sulfated glycosaminoglycans compared with cdECMs. Structural characteristics revealed an immature state of the fibrous part of cdECM samples. By the identified differences, we aim to support researchers in the selection of a suitable ECM-based biomaterial for their specific application and the interpretation of obtained results.
This study empirically analyzes and compares return data from developed and emerging market data based on the Fama French five-factor model and compares it to previous results from the Fama French three-factor model by Kostin, Runge and Adams (2021). It researches whether the addition of the profitability and investment pattern factors show superior results in the assessment of emerging markets during the COVID-19 pandemic compared to developed markets. We use panel data covering eight indices of developed and emerging countries as well as a selection of eight companies from these markets, covering a period from 2000 to 2020. Our findings suggest that emerging markets do not generally outperform developed markets. The results underscore the need to reconsider the assumption that adding more factors to regression models automatically yields results that are more reliable. Our study contributes to the extant literature by broadening this research area. It is the first study to compare the performance of the Fama French three-factor model and the Fama French five-factor model in the cost of equity calculation for developed and emerging countries during the COVID-19 pandemic and other crisis events of the past two decades.
Gewinn, Profitabilität und Wachstum eines Unternehmens sind untrennbar mit dem Arbeitseinsatz und der Mitarbeiterperformance verbunden (Birri, 2014; Bligh et al., 2006). Arbeitseinsatz und Performance wiederum erwachsen maßgeblich aus den grundlegenden intrinsischen und extrinsischen Motivationstreibern. Also müssen Unternehmen zur Sicherung ihres Erfolgs mit geeigneten Werkzeugen gezielt auf diese Treiber einwirken. Ein zentrales Werkzeug hierfür sind die Vergütungssysteme der Unternehmen.
The world population is growing and alternative ways of satisfying the increasing demand for meat are being explored, such as using animal cells for the fabrication of cultured meat. Edible biomaterials are required as supporting structures. Hence, we chose agarose, gellan and a xanthan-locust bean gum blend (XLB) as support materials with pea and soy protein additives and analyzed them regarding material properties and biocompatibility. We successfully built stable hydrogels containing up to 1% pea or soy protein. Higher amounts of protein resulted in poor handling properties and unstable gels. The gelation temperature range for agarose and gellan blends is between 23–30 °C, but for XLB blends it is above 55 °C. A change in viscosity and a decrease in the swelling behavior was observed in the polysaccharide-protein gels compared to the pure polysaccharide gels. None of the leachates of the investigated materials had cytotoxic effects on the myoblast cell line C2C12. All polysaccharide-protein blends evaluated turned out as potential candidates for cultured meat. For cell-laden gels, the gellan blends were the most suitable in terms of processing and uniform distribution of cells, followed by agarose blends, whereas no stable cell-laden gels could be formed with XLB blends.
Up to now biorefinery concepts can hardly compete with the conventional production of fossil-based chemicals. On one hand, conventional chemical production has been optimised over many decades in terms of energy, yield and costs. Biorefineries, on the other hand, do not have the benefit of long-term experience and therefore have a huge potential for optimisation. This study deals with the economic evaluation of a newly developed biorefinery concept based on superheated steam (SHS) torrefaction of biomass residues with recovery of valuable platform chemicals. Two variants of the biorefinery were economically investigated. One variant supplies various platform chemicals and torrefied biomass. The second variant supplies thermal energy for external consumers in addition to platform chemicals. The results show that both variants can be operated profitably if the focus of the platform chemicals produced is on high quality and thus on the higher-priced segment. The economic analysis gives clear indications of the most important financial influencing parameters. The economic impact of integration into existing industrial structures is positive. With the analysis, a viable business model can be developed. Based on the results of the present study, an open-innovation platform is recommended for the further development and commercialisation of the novel biorefinery.
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.
Commercially available homogenized cow- and plant-based milks were investigated by optical spectroscopy in the range of 400–1360 nm. Absorbance spectra, the effective scattering coefficient μs′, and the spectral absorption coefficient μa were recorded for 23 milk varieties and analyzed by multivariate data analysis. Cow- and plant-based milks were compared and discriminated using principal component analysis combined with a quadratic discriminant analysis. Furthermore, it was possible to discriminate the origin of plant-based milk by μa and the fat content in cow-based milk by μs′. Partial least squares regression models were developed to determine the fat content in cow-based milk. The model for μs′ proved to be the most efficient for this task with R2 = 0.98 and RMSEP = 0.19 g/100 mL for the external validation. Thus, optical spectroscopy together with multivariate data analysis is suitable for routine laboratory analysis or quality monitoring in the dairy production.