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Digitalization, as well as sustainability, are gaining increased relevance and have attracted significant attention in research and practice. However, the research already published about this topic examining digitalization in the retail sector does not consider the acceptance of related innovations, nor their impact on sustainability. Therefore, this article critically analyzes the acceptance of customers towards digital technologies in fashion stores as well as their impact on sustainability in the textile industry. The comprehensive analysis of the literature and the current state of research provide the basis of this paper. Theoretical models, such as the Technology-Acceptance-Model (TAM) and the Unified Theory of Acceptance and Use of Technology 2 (UTAUT 2) enable the evaluation of expectations and acceptance, as well as the assessment of possible inhibitory factors for the subsequent descriptive and statistical examination of the acceptance of digital technologies in fashion stores. The research on this subject was examined in a quantitative way. The key findings show that customers do accept digital technologies in fashion stores. The final part of this contribution describes the innovative Digitalization 4 Sustainability Framework which shows that digital technologies at the point of sale (PoS) in fashion stores could have a positive impact on sustainability. Overall, this paper shows that it is particularly important for fashion stores to concentrate on their individual strengths and customer needs as well as to indicate a more sustainable way by using digital technologies, in order to achieve added value for the customers and to set themselves apart from the competition while designing a more sustainable future. Moreover, fashion stores should make it a point of their honor to harness the power of digitalization for sake of sustainability and economic value creation.
Digitalization, as well as sustainability, are gaining increased relevance and have attracted significant attention in research and practice. However, the research already published about this topic examining digitalization in the retail sector does not consider the acceptance of related innovations, nor their impact on sustainability. Therefore, this article critically analyzes the acceptance of customers towards digital technologies in fashion stores as well as their impact on sustainability in the textile industry. The comprehensive analysis of the literature and the current state of research provide the basis of this paper. Theoretical models, such as the Technology-Acceptance-Model (TAM) and the Unified Theory of Acceptance and Use of Technology 2 (UTAUT 2) enable the evaluation of expectations and acceptance, as well as the assessment of possible inhibitory factors for the subsequent descriptive and statistical examination of the acceptance of digital technologies in fashion stores. The research on this subject was examined in a quantitative way. The key findings show that customers do accept digital technologies in fashion stores. The final part of this contribution describes the innovative Digitalization 4 Sustainability Framework which shows that digital technologies at the point of sale (PoS) in fashion stores could have a positive impact on sustainability. Overall, this paper shows that it is particularly important for fashion stores to concentrate on their individual strengths and customer needs as well as to indicate a more sustainable way by using digital technologies, in order to achieve added value for the customers and to set themselves apart from the competition while designing a more sustainable future. Moreover, fashion stores should make it a point of their honor to harness the power of digitalization for sake of sustainability and economic value creation.
During the last few decades, the rapid separation of the Small Aral Sea from the isolated basin has changed its hydrological and ecological conditions tremendously. In the present study, we developed and validated the hybrid model for the Syr Darya River basin based on a combination of state-of-the-art hydrological and machine learning models. Climate change impact on freshwater inflow into the Small Aral Sea for the projection period 2007–2099 has been quantified based on the developed hybrid model and bias corrected and downscaled meteorological projections simulated by four General Circulation Models (GCM) for each of three Representative Concentration Pathway scenarios (RCP). The developed hybrid model reliably simulates freshwater inflow for the historical period with a Nash–Sutcliffe efficiency of 0.72 and a Kling–Gupta efficiency of 0.77. Results of the climate change impact assessment showed that the freshwater inflow projections produced by different GCMs are misleading by providing contradictory results for the projection period. However, we identified that the relative runoff changes are expected to be more pronounced in the case of more aggressive RCP scenarios. The simulated projections of freshwater inflow provide a basis for further assessment of climate change impacts on hydrological and ecological conditions of the Small Aral Sea in the 21st Century.
Higher eco-efficiency will not be enough to slow global warming caused by climate change. To keep global warming to 2 degrees, people also need to reduce their consumption. At present, however, many who would be able to do so seem unwilling to comply. Given the threats of a runaway climate change, urgent measures are needed to promote less personal consumption. This study, therefore, examines whether social marketing consume-less appeals can be used to encourage consumers to voluntarily abstain from consumption. As part of an online experiment with nearly 2000 randomly sampled users of an online platform for sustainable consumption, we tested the effectiveness of five different “consume-less” appeals based on traditional advertising formats (including emotional, informational, and social claims). The study shows that consume-less appeals are capable of limiting personal desire to buy. However, significant differences in the effectiveness of the appeal formats used in this study were observed. In addition, we found evidence of rebound effects, which leads us to critically evaluate the overall potential of social marketing to promote more resource-conserving lifestyles. While commercial consumer-free appeals have previously been studied (e.g., Patagonia’s “Don’t Buy This Jacked”), this study on the effectiveness of non-commercial consume-free appeals is novel and provides new insights.
Less is more!
(2021)
Enhancing consumer satisfaction and well-being is an important objective of companies, retailers and public policy makers. In the current debate on climate change, a consistent theme is that consumers in developed countries must learn to consume less. The present study (based on representative data sets from the US, N = 1,017, and Germany, N = 1030) addresses these issues by using a scenario-based experiment to analyze how satisfied voluntary simplifiers (people who voluntarily abstain from consumption) are with their purchase decisions in the case of a muesli brand. The research question is whether people who follow a sustainable, simple lifestyle are more satisfied with their daily consumption choices than people who have a more consumerist lifestyle. If so, it would be easier for many people to change their lifestyles and consume less. In addition, this scenario experiment manipulates consumer empowerment and decision complexity since both factors are supposed to influence purchase satisfaction. The results are consistent across both countries and indicate that voluntary simplifiers experience a higher level of purchasing satisfaction than non-simplifiers, whereby empowerment and decision complexity play different roles.
Bank filtration is considered to improve water quality through microbially mediated degradation of pollutants and is suitable for waterworks to increase their production. In particular, aquifer temperatures and oxygen supply have a great impact on many microbial processes. To investigate the temporal and spatial behavior of selected organic micropollutants during bank filtration in dependence of relevant biogeochemical conditions, we have set up a 2D reactive transport model using MODFLOW and PHT3D under the user interface ORTI3D. The considered 160-m-long transect ranges from the surface water to a groundwater extraction well of the adjacent waterworks. For this purpose, water levels, temperatures, and chemical parameters were regularly measured in the surface water and groundwater observation wells over one and a half years. To simulate the effect of seasonal temperature variations on microbial mediated degradation, we applied an empirical temperature factor, which yields a strong reduction of the degradation rate at groundwater temperatures below 11 degrees C. Except for acesulfame, the considered organic micropollutants are substantially degraded along their subsurface flow paths with maximum degradation rates in the range of 10(-6) mol L-1 s(-1). Preferential biodegradation of phenazone, diclofenac, and valsartan was found under oxic conditions, whereas carbamazepine and sulfamethoxazole were degraded under anoxic conditions. This study highlights the influence of seasonal variations in oxygen supply and temperature on the fate of organic micropollutants in surface water infiltrating into an aquifer.
Assessment of climate change impact on discharge of the lakhmass catchment (Northwest Tunisia)
(2022)
The Mediterranean region is increasingly recognized as a climate change hotspot but is highly underrepresented in hydrological climate change studies. This study aims to investigate the climate change effects on the hydrology of Lakhmass catchment in Tunisia. Lakhmass catchment is a part of the Medium Valley of Medjerda in northwestern Tunisia that drains an area of 126 km(2). First, the Hydrologiska Byrans Vattenbalansavdelning light (HBV-light) model was calibrated and validated successfully at a daily time step to simulate discharge during the 1981-1986 period. The Nash Sutcliffe Efficiency and Percent bias (NSE, PBIAS) were (0.80, +2.0%) and (0.53, -9.5%) for calibration (September 1982-August 1984) and validation (September 1984-August 1986) periods, respectively. Second, HBV-light model was considered as a predictive tool to simulate discharge in a baseline period (1981-2009) and future projections using data (precipitation and temperature) from thirteen combinations of General Circulation Models (GCMs) and Regional Climatic Models (RCMs). We used two trajectories of Representative Concentration Pathways, RCP4.5 and RCP8.5, suggested by the Intergovernmental Panel on Climate Change (IPCC). Each RCP is divided into three projection periods: near-term (2010-2039), mid-term (2040-2069) and long-term (2070-2099). For both scenarios, a decrease in precipitation and discharge will be expected with an increase in air temperature and a reduction in precipitation with almost 5% for every +1 degrees C of global warming. By long-term (2070-2099) projection period, results suggested an increase in temperature with about 2.7 degrees C and 4 degrees C, and a decrease in precipitation of approximately 7.5% and 15% under RCP4.5 and RCP8.5, respectively. This will likely result in a reduction of discharge of 12.5% and 36.6% under RCP4.5 and RCP8.5, respectively. This situation calls for early climate change adaptation measures under a participatory approach, including multiple stakeholders and water users.
Energy system developments and investments in the decisive decade for the Paris Agreement goals
(2021)
The Paris Agreement does not only stipulate to limit the global average temperature increase to well below 2 °C, it also calls for 'making finance flows consistent with a pathway towards low greenhouse gas emissions'. Consequently, there is an urgent need to understand the implications of climate targets for energy systems and quantify the associated investment requirements in the coming decade. A meaningful analysis must however consider the near-term mitigation requirements to avoid the overshoot of a temperature goal. It must also include the recently observed fast technological progress in key mitigation options. Here, we use a new and unique scenario ensemble that limit peak warming by construction and that stems from seven up-to-date integrated assessment models. This allows us to study the near-term implications of different limits to peak temperature increase under a consistent and up-to-date set of assumptions. We find that ambitious immediate action allows for limiting median warming outcomes to well below 2 °C in all models. By contrast, current nationally determined contributions for 2030 would add around 0.2 °C of peak warming, leading to an unavoidable transgression of 1.5 °C in all models, and 2 °C in some. In contrast to the incremental changes as foreseen by current plans, ambitious peak warming targets require decisive emission cuts until 2030, with the most substantial contribution to decarbonization coming from the power sector. Therefore, investments into low-carbon power generation need to increase beyond current levels to meet the Paris goals, especially for solar and wind technologies and related system enhancements for electricity transmission, distribution and storage. Estimates on absolute investment levels, up-scaling of other low-carbon power generation technologies and investment shares in less ambitious scenarios vary considerably across models. In scenarios limiting peak warming to below 2 °C, while coal is phased out quickly, oil and gas are still being used significantly until 2030, albeit at lower than current levels. This requires continued investments into existing oil and gas infrastructure, but investments into new fields in such scenarios might not be needed. The results show that credible and effective policy action is essential for ensuring efficient allocation of investments aligned with medium-term climate targets.
A conundrum of trends
(2022)
This comment is meant to reiterate two warnings: One applies to the uncritical use of ready-made (openly available) program packages, and one to the estimation of trends in serially correlated time series. Both warnings apply to the recent publication of Lischeid et al. about lake-level trends in Germany.