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Over the past decade, the proliferation of entrepreneurial ventures and small firms with sustainable business models have pushed the sustainability agenda in the fashion industry. Despite prominent success stories, these companies often encounter significant operative challenges that hinder growth or even cause business failure. This paper adopts a qualitative research design and uses data gathered during 18 expert interviews with entrepreneurs and executive managers of 18 firms from 13 countries to identify and explore the dominant challenges that micro- and small-sized sustainable fashion companies struggle with. The results indicate that communicating with consumers is perceived as surprisingly difficult, especially because sustainable brands need to justify higher prices and explain the added benefits of their products. Second, resource constraints lead to operative friction and overburdening of the decision makers and their small management teams. Third, sustainable sourcing and production processes are economically difficult in an industry that continues to occupy a mass and low-cost logic. Against the background of these insights, a range of managerial recommendations are developed and contextualized in the framework of the Business Model Canvas. This novel approach makes the suggestions which are rooted in the resource-based view actionable and supports sustainable businesses to better manage their operations and achieve growth. For example, collaborative approaches with different stakeholders may mitigate constraints across all three identified problem areas.
In recent years, various studies have highlighted the opportunities of artificial intelligence (AI) for our society. For example, AI solutions can help reduce pollution, waste, or carbon footprints. On the other hand, there are also risks associated with the use of AI, such as increasing inequality in society or high resource consumption for computing power. This paper explores the question how corporate culture influences the use of artificial intelligence in terms of sustainable development. This type of use includes a normative element and is referred to in the paper as sustainable artificial intelligence (SAI). Based on a bibliometric literature analysis, we identify features of a sustainability-oriented corporate culture. We offer six propositions examining the influence of specific manifestations on the handling of AI in the sense of SAI. Thus, if companies want to ensure that SAI is realized, corporate culture appears as an important indicator and influencing factor at the same time.
Information systems (IS) play a central role in promoting corporate sustainability and pro-environmental behavior. This study explores the use of mobile apps for fostering sustainability-oriented corporate culture. It accentuates issues relating to sustainability-oriented corporate culture (RQ1), app meta-requirements as a strategic approach to addressing these issues (RQ2), as well as design and implementation principles (RQ3). Referring to the literature on sustainability apps, gamification, and nudging, our qualitative research design combines an analysis of four corporate apps intending to promote sustainable behavior and expert interviews (Grounded Theory). The proposed framework supports the planning, realization, and monitoring of this targeted app use. Single cultural dimensions inform seven issues in culture development. Five meta-requirements address this multi-dimensionality, challenges provided by new digital working environments, and principles of Green IT. Four design principles support, extend, and integrate current knowledge on app features, nudging, and gamification. Five variables determine the app intervention and maturity level. We conclude that this targeted app use should intend to foster the sustainability orientation within all dimensions of corporate culture instead of being limited to promoting sustainable behavior.
HRM processes are increasingly AI-driven, and HRM supports the general digital transformation of companies’ viable competitiveness. This paper points out possible positive and negative effects on HRM, workplaces, and workersorganizations along the HR processes and its potential for competitive advantage in regard to managerial decisions on AI implementation regarding augmentation and automation of work.
A systematic literature review that includes 62 international journals across different disciplines and contains top-tier academic and German practitioner journals was conducted. The literature analysis applies the resource-based view (RBV) as a lens through which to explore AI-driven HRM as a potential source of organizational capabilities.
The analysis shows four ambiguities for AI-driven HRM that might support sustainable company development or might prevent AI application: job design, transparency, performance and data ambiguity. A limited scholarly discussion with very few empirical studies can be stated. To date, research has mainly focused on HRM in general, recruiting, and HR analytics in particular.
The four ambiguities’ context-specific potential for capability building in firms is indicated, and research avenues are developed.
This paper critically explores AI-driven HRM and structures context-specific potential for capability building along four ambiguities that must be addressed by HRM to strategically contribute to an organization’s competitive advantage.
Aims and Objectives:
Preventive home visits are a low-threshold counselling and support approach. They have been reported to achieve heterogeneous effects. However, preventive home visits have the potential to reduce the risk of becoming dependent on long-term care. The aim of this study is to investigate the effect of preventive home visits as a nursing intervention on health-related quality of life of older people in a longitudinal survey and to develop recommendations for which target groups preventive home visits have the highest benefit. The sample consisted of 75 people, aged between 65 and 85, who were able to understand and speak German, had not yet been eligible for benefits from the long-term care insurance and lived in the municipality under study.
Methodological Design and Justification:
A quantitative longitudinal study in order to investigate the effects of preventive home visits.
Ethical Issues and Approval:
There were no ethical concerns. Accordingly, ethical approval was granted.
Research Methods, Results and Conclusions:
The health-related quality of life was recorded four times between 01/2017 and 08/2020 with the Short-Form- Health- Survey- 12 and analysed using descriptive statistics. Results reveal that the physical health status cannot be easily influenced over a short period of time. The main effect, however, is that preventive home visits have a significant positive effect on the mental health status. The main topics during the home visits were mobility, nutrition and social participation. Increased knowledge and motivation for preventive behaviour extended the autonomy of older people. Accordingly, preventive home visits can support a self-determined life in a familiar environment. The results of the present study show that preventive home visits as a nursing intervention in rural areas are successful. In Germany, preventive home visits have not yet been implemented on a regular basis. In order to do so, a general definition of the concept is needed. Preventive home visits should be officially included in the regular health care services in Germany.
The distribution of a species along a thermal gradient is commonly approximated by a unimodal response curve, with a characteristic single optimum near the tempera‐ture where a species is most likely to be found, and a decreasing probability of occur‐rence away from the optimum. We aimed at identifying thermal response curves (TRCs) of European freshwater species and evaluating the potential impact of climate warming across species, taxonomic groups, and latitude. We first applied generalized additive models using catchment‐scale global data on distribution ranges of 577 freshwater species native to Europe and four different temperature variables (the current annual mean air/water temperature and the maximum air/water temperature of the warmest month) to describe species TRCs. We then classified TRCs into one of eight curve types and identified spatial patterns in thermal responses. Finally, we in‐tegrated empirical TRCs and the projected geographic distribution of climate warm‐ing to evaluate the effect of rising temperatures on species’ distributions. For the different temperature variables, 390–463 of 577 species (67.6%–80.2%) were char‐acterized by a unimodal TRC. The number of species with a unimodal TRC decreased from central toward northern and southern Europe. Warming tolerance (WT = maxi‐mum temperature of occurrence—preferred temperature) was higher at higher lati‐tudes. Preferred temperature of many species is already exceeded. Rising temperatures will affect most Mediterranean species. We demonstrated that fresh‐water species’ occurrence probabilities are most frequently unimodal. The impact of the global climate warming on species distributions is species and latitude depend‐ent. Among the studied taxonomic groups, rising temperatures will be most detri‐mental to fish. Our findings support the efforts of catchment‐based freshwater management and conservation in the face of global warming.
Niche-based species distribution models (SDMs) have become an essential tool in conservation and restoration planning. Given the current threats to freshwater biodiversity, it is of fundamental importance to address scale effects on the performance of niche-based SDMs of freshwater species’ distributions. The scale effects are addressed here in the context of hierarchical catchment ordering, considered as counterpart to coarsening grain-size by increasing grid-cell size. We combine fish occurrence data from the Danube River Basin, the hierarchical catchment ordering and multiple environmental factors representing topographic, climatic and anthropogenic effects to model fish occurrence probability across multiple scales. We focus on 1st to 5th order catchments. The spatial scale (hierarchical catchment order) only marginally influences the mean performance of SDMs, however the uncertainty of the estimates increases with scale. Key predictors and their relative importance are scale and species dependent. Our findings have useful implications for choosing proper species dependent spatial scales for river rehabilitation measures, and for conservation planning in areas where fine grain species data are unavailable.
Land cover change is a dynamic phenomenon driven by synergetic biophysical and socioeconomic effects. It involves massive transitions from natural to less natural habitats and thereby threatens ecosystems and the services they provide. To retain intact ecosystems and reduce land cover change to a minimum of natural transition processes, a dense network of protected areas has been established across Europe. However, even protected areas and in particular the zones around protected areas have been shown to undergo land cover changes. The aim of our study was to compare land cover changes in protected areas, non-protected areas, and 1 km buffer zones around protected areas and analyse their relationship to climatic and socioeconomic factors across Europe between 2000 and 2012 based on earth observation data. We investigated land cover flows describing major change processes: urbanisation, afforestation, deforestation, intensification of agriculture, extensification of agriculture, and formation of water bodies. Based on boosted regression trees, we modelled correlations between land cover flows and climatic and socioeconomic factors. The results show that land cover changes were most frequent in 1 km buffer zones around protected areas (3.0% of all buffer areas affected). Overall, land cover changes within protected areas were less frequent than outside, although they still amounted to 18,800 km2 (1.5% of all protected areas) from 2000 to 2012. In some parts of Europe, urbanisation and intensification of agriculture still accounted for up to 25% of land cover changes within protected areas. Modelling revealed meaningful relationships between land cover changes and a combination of influencing factors. Demographic factors (accessibility to cities and population density) were most important for coarse-scale patterns of land cover changes, whereas fine-scale patterns were most related to longitude (representing the general east/west economic gradient) and latitude (representing the north/south climatic gradient).
Thermal response curves that depict the probability of occurrence along a thermal gradient are used to derive various species’ thermal properties and abilities to cope with warming. However, different thermal responses can be expected for different portions of a species range. We focus on differences in thermal response curves (TRCs) and thermal niche requirements for four freshwater fishes (Coregonus sardinella, Pungitius pungitius, Rutilus rutilus, Salvelinus alpinus) native to Europe at (1) the global and (2) European continental scale. European ranges captured only a portion of the global thermal range with major differences in the minimum (Tmin), maximum (Tmax) and average temperature (Tav) of the respective distributions. Further investigations of the model-derived preferred temperature (Tpref), warming tolerance (WT = Tmax − Tpref), safety margin (SM = Tpref − Tav) and the future climatic impact showed substantially differing results. All considered thermal properties either were under- or overestimated at the European level. Our results highlight that, although continental analyses have an impressive spatial extent, they might deliver misleading estimates of species thermal niches and future climate change impacts, if they do not cover the full species ranges. Studies and management actions should therefore favor whole global range distribution data for analyzing species responses to environmental gradients.
Freshwater ecosystems host disproportionately high numbers of species relative to their surface area yet are poorly protected globally. We used data on the distribution of 1631 species of aquatic plant, mollusc, odonate and fish in 18,816 river and lake catchments in Europe to establish spatial conservation priorities based on the occurrence of threatened, rangerestricted and endemic species using the Marxan systematic conservation planning tool. We found that priorities were highest for rivers and ancient lakes in S Europe, large rivers and lakes in E and N Europe, smaller lakes in NW Europe and karst/limestone areas in the Balkans, S France and central Europe. The a priori inclusion of well-protected catchments resulted in geographically more balanced priorities and better coverage of threatened (critically endangered, endangered and vulnerable) species. The a priori exclusion of well-protected catchments showed that priority areas that need further conservation interventions are in S and E Europe. We developed three ways to evaluate the correspondence between conservation priority and current protection by assessing whether a cathment has more (or less) priority given its protection level relative to all other catchments. Each method found that priority relative to protection was high in S and E Europe and generally low in NW Europe. The inclusion of hydrological connectivity had little influence on these patterns but decreased the coverage of threatened species, indicating a trade-off between connectivity and conservation of threatened species. Our results suggest that catchments in S and E Europe need urgent conservation attention (protected areas, restoration, management, species protection) in the face of imminent threats such as river regulation, dam construction, hydropower development and climate change. Our study presents continental-scale conservation priorities for freshwater ecosystems in ecologically meaningful planning units and will thus be important in freshwater biodiversity conservation policy and practice, and water management in Europe.